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This article describes the development of a method to localize an athlete during sports performance on a platform, based on a static video recording. Considered sport for this method is wushu – martial art. However, any other discipline can be applied. There are specified requirements, and 2 algorithms of image processing are described. The next part presents an experiment that was held based on recordings from the Pan American Wushu Championship. Based on those recordings the steps of the algorithm are shown. Results are evaluated manually. The last part of the article concludes if the algorithm is applicable and what improvements have to be implemented to use it during sports competitions as well as for offline analysis.

The introduction of the System-on-Chip (SoC) technology has brought exciting new opportunities for the development of smart low cost embedded systems spanning a wide range of applications. Currently available SoC devices are capable of performing high speed digital signal processing tasks in software while featuring relatively low development costs and reduced time-to-market. Unmanned aerial vehicles (UAV) are an application example that has shown tremendous potential in an increasing number of scenarios, ranging from leisure to surveillance as well as in search and rescue missions. Video capturing from UAV platforms is a relatively straightforward task that requires almost no preprocessing. However, that does not apply to audio signals, especially in cases where the data is to be used to support real-time decision making. In fact, the enormous amount of acoustic interference from the surroundings, including the noise from the UAVs propellers, becomes a huge problem. This paper discusses a real-time implementation of the NLMS adaptive filtering algorithm applied to enhancing acoustic signals captured from UAV platforms. The model relies on a combination of acoustic sensors and a computational inexpensive algorithm running on a digital signal processor. Given its simplicity, this solution can be incorporated into the main processing system of an UAV using the SoC technology, and run concurrently with other required tasks, such as flight control and communications. Simulations and real-time DSP-based implementations have shown significant signal enhancement results by efficiently mitigating the interference from the noise generated by the UAVs propellers as well as from other external noise sources.

Automatic identification of television programs in the TV stream is an important task for operating archives. This article proposes a new spatio-temporal approach to identify the programs in TV stream into two main steps: First, a reference catalogue for video features visual jingles built. We operate the features that characterize the instances of the same program type to identify the different types of programs in the flow of television. The role of video features is to represent the visual invariants for each visual jingle using appropriate automatic descriptors for each television program. On the other hand, programs in television streams are identified by examining the similarity of the video signal for visual grammars in the catalogue. The main idea of the identification process is to compare the visual similarity of the video signal features in the flow of television to the catalogue. After presenting the proposed approach, the paper overviews encouraging experimental results on several streams extracted from different channels and compounds of several programs.

In this paper, we propose a high definition video display format conversion system based on FPGA which converts the Camera Link format video data (1928×1084, progressive scanning, 33 fps) into the HDMI format video (1920×1080p, 30 fps), and then output to the HD display device with a HDMI interface. This system can solve the display incompatible problem between different HD video frame rates. Experimental results show that the proposed system realizes a real-time video format conversion; furthermore, the output video image has a good quality.

Ultra-high speed (UHS) CMOS image sensors with on-chop analog memories placed on the periphery of pixel array for the visualization of UHS phenomena are overviewed in this paper. The developed UHS CMOS image sensors consist of 400H×256V pixels and 128 memories/pixel, and the readout speed of 1Tpixel/sec is obtained, leading to 10 Mfps full resolution video capturing with consecutive 128 frames, and 20 Mfps half resolution video capturing with consecutive 256 frames. The first development model has been employed in the high speed video camera and put in practical use in 2012. By the development of dedicated process technologies, photosensitivity improvement and power consumption reduction were simultaneously achieved, and the performance improved version has been utilized in the commercialized high-speed video camera since 2015 that offers 10 Mfps with ISO16,000 photosensitivity. Due to the improved photosensitivity, clear images can be captured and analyzed even under low light condition, such as under a microscope as well as capturing of UHS light emission phenomena.

The fish embryo toxicity (FET) biotest performed on embryos of zebrafish (Danio rerio) has gained significant popularity as a rapid and inexpensive alternative approach in chemical hazard and risk assessment. The FET was designed to evaluate acute toxicity on embryonic stages of fish exposed to the test chemical. The current standard, similar to most traditional methods for evaluating aquatic toxicity provides, however, little understanding of effects of environmentally relevant concentrations of chemical stressors. We postulate that significant environmental effects such as altered motor functions, physiological alterations reflected in heart rate, effects on development and reproduction can occur at sub-lethal concentrations well below than LC10. Behavioral studies can, therefore, provide a valuable integrative link between physiological and ecological effects. Despite the advantages of behavioral analysis development of behavioral toxicity, biotests is greatly hampered by the lack of dedicated laboratory automation, in particular, user-friendly and automated video microscopy systems. In this work we present a proof-of-concept development of an optical system capable of tracking embryonic vertebrates behavioral responses using automated and vastly miniaturized time-resolved video-microscopy. We have employed miniaturized CMOS cameras to perform high definition video recording and analysis of earliest vertebrate behavioral responses. The main objective was to develop a biocompatible embryo positioning structures that were suitable for high-throughput imaging as well as video capture and video analysis algorithms. This system should support the development of sub-lethal and behavioral markers for accelerated environmental monitoring.

In this paper, an embedded system for remote online video monitoring was designed and developed to capture and record the real-time circumstances in elevator. For the purpose of improving the efficiency of video acquisition and processing, the system selected Samsung S5PV210 chip as the core processor which Integrated graphics processing unit. And the video was encoded with H.264 format for storage and transmission efficiently. Based on S5PV210 chip, the hardware video coding technology was researched, which was more efficient than software coding. After running test, it had been proved that the hardware video coding technology could obviously reduce the cost of system and obtain the more smooth video display. It can be widely applied for the security supervision [1].

This paper presents a comparison of YUV color video formats using the H.264 video compression standard. The goal of this paper is to determine the best color video format for rate-distortion quality. This is a point of interest due to wireless video transmission quality and bandwidth limitations. The results show that for 1080p video, the YUV 4:2:0 video with a chrominance quantization parameter offset of zero is among the best performing color video format in terms of rate-distortion quality for three different levels of compression and two different entropy encodings.

Voluminous amount of videos in today’s world has made the subject of objective (or semi-objective) classification of videos to be very popular. Among the various descriptors used for video classification, SIFT and LIFT can lead to highly accurate classifiers. But, SIFT descriptor does not consider video motion and LIFT is time-consuming. In this paper, a robust descriptor for semi-supervised classification based on video content is proposed. It holds the benefits of LIFT and SIFT descriptors and overcomes their shortcomings to some extent. For extracting this descriptor, the SIFT descriptor is first used and the motion of the extracted keypoints are then employed to improve the accuracy of the subsequent classification stage. As SIFT descriptor is scale invariant, the proposed method is also robust toward zooming. Also, using the global motion of keypoints in videos helps to neglect the local motions caused during video capturing by the cameraman. In comparison to other works that consider the motion and mobility of videos, the proposed descriptor requires less computations. Obtained results on the TRECVIT 2006 dataset show that the proposed method achieves more accurate results in comparison with SIFT in content-based video classifications by about 15 percent.

This paper presents a FPGA based video interface conversion system that enables the inter-conversion between digital and analog video. Cyclone IV series EP4CE22F17C chip from Altera Corporation is used as the main video processing chip, and single-chip is used as the information interaction control unit between FPGA and PC. The system is able to encode/decode messages from the PC. Technologies including video decoding/encoding circuits, bus communication protocol, data stream de-interleaving and de-interlacing, color space conversion and the Camera Link timing generator module of FPGA are introduced. The system converts Composite Video Broadcast Signal (CVBS) from the CCD camera into Low Voltage Differential Signaling (LVDS), which will be collected by the video processing unit with Camera Link interface. The processed video signals will then be inputted to system output board and displayed on the monitor.The current experiment shows that it can achieve high-quality video conversion with minimum board size.

Combining with the current development trend in video surveillance-digitization and high-definition, a multimode-compatible image acquisition system for HD area array CCD is designed. The hardware and software designs of the color video capture system of HD area array CCD KAI-02150 presented by Truesense Imaging company are analyzed, and the structure parameters of the HD area array CCD and the color video gathering principle of the acquisition system are introduced. Then, the CCD control sequence and the timing logic of the whole capture system are realized. The noises of the video signal (KTC noise and 1/f noise) are filtered by using the Correlated Double Sampling (CDS) technique to enhance the signal-to-noise ratio of the system. The compatible designs in both software and hardware for the two other image sensors of the same series: KAI-04050 and KAI-08050 are put forward; the effective pixels of these two HD image sensors are respectively as many as four million and eight million. A Field Programmable Gate Array (FPGA) is adopted as the key controller of the system to perform the modularization design from top to bottom, which realizes the hardware design by software and improves development efficiency. At last, the required time sequence driving is simulated accurately by the use of development platform of Quartus Ⅱ12.1 combining with VHDL. The result of the simulation indicates that the driving circuit is characterized by simple framework, low power consumption, and strong anti-interference ability, which meet the demand of miniaturization and high-definition for the current tendency.

This paper presents a high‐definition video display solution based on the FPGA and THS8200. THS8200 is a video decoder chip launched by TI company, this chip has three 10-bit DAC channels which can capture video data in both 4:2:2 and 4:4:4 formats, and its data synchronization can be either through the dedicated synchronization signals HSYNC and VSYNC, or extracted from the embedded video stream synchronization information SAV / EAV code. In this paper, we will utilize the address and control signals generated by FPGA to access to the data‐storage array, and then the FPGA generates the corresponding digital video signals YCbCr. These signals combined with the synchronization signals HSYNC and VSYNC that are also generated by the FPGA act as the input signals of THS8200. In order to meet the bandwidth requirements of the high‐definition TV, we adopt video input in the 4:2:2 format over 2×10-bit interface. THS8200 is needed to be controlled by FPGA with I 2 C bus to set the internal registers, and as a result, it can generate the synchronous signal that is satisfied with the standard SMPTE and transfer the digital video signals YCbCr into analog video signals YPbPr. Hence, the composite analog output signals YPbPr are consist of image data signal and synchronous signal which are superimposed together inside the chip THS8200. The experimental research indicates that the method presented in this paper is a viable solution for high‐definition video display, which conforms to the input requirements of the new high‐definition display devices.

We present a method for distinguishing human face from high-emulation mask, which is increasingly used by criminals for activities such as stealing card numbers and passwords on ATM. Traditional facial recognition technique is difficult to detect such camouflaged criminals. In this paper, we use the high-resolution hyperspectral video capture system to detect high-emulation mask. A RGB camera is used for traditional facial recognition. A prism and a gray scale camera are used to capture spectral information of the observed face. Experiments show that mask made of silica gel has different spectral reflectance compared with the human skin. As multispectral image offers additional spectral information about physical characteristics, high-emulation mask can be easily recognized.

As people's life quality have been improved significantly, the traditional 2D video technology can not meet people's urgent desire for a better video quality, which leads to the rapid development of 3D video technology. Simultaneously people want to watch 3D video in portable devices,. For achieving the above purpose, we set up a remote stereoscopic video play platform. The platform consists of a server and clients. The server is used for transmission of different formats of video and the client is responsible for receiving remote video for the next decoding and pixel restructuring. We utilize and improve Live555 as video transmission server. Live555 is a cross-platform open source project which provides solutions for streaming media such as RTSP protocol and supports transmission of multiple video formats. At the receiving end, we use our laboratory own player. The player for Android, which is with all the basic functions as the ordinary players do and able to play normal 2D video, is the basic structure for redevelopment. Also RTSP is implemented into this structure for telecommunication. In order to achieve stereoscopic display, we need to make pixel rearrangement in this player's decoding part. The decoding part is the local code which JNI interface calls so that we can extract video frames more effectively. The video formats that we process are left and right, up and down and nine grids. In the design and development, a large number of key technologies from Android application development have been employed, including a variety of wireless transmission, pixel restructuring and JNI call. By employing these key technologies, the design plan has been finally completed. After some updates and optimizations, the video player can play remote 3D video well anytime and anywhere and meet people's requirement.

A large number of remote video sensors are being deployed in the world to collect, store, and analyze the real-world data. Since a remote video sensor produces very large data, the total amount of video data are extremely large in size, complexity, and capacity. Important events from a remote video sensor are closely related to a motion in video. We present, in this paper, a fast motion detection method based on the number of bits used for encoding a video stream and the GOP-level motion detection. A low complexity measurement of the number of bits is performed in the coded video sequence and then, we store and process the coded video stream only if the total bits are larger than a pre-defined threshold. We also use a GOP level motion detection to reduce processing overhead compared to the conventional motion vector-based approach which processes every frame. Manipulating the number of bits is itself a much easier task than full reconstruction of each pixel of a video frame and it can save storage cost because it only stores a coded video sequence with a motion. The proposed method also contributes to reduction of computational complexity compared to the manipulation of motion vectors per 4x4 macro block. To evaluate our method, we deployed a centralized single server connected to H.264 capable remote video sensors. Results on the video sequences showed that the proposed approach can process more video sequences than the conventional compressed domain approach.

This paper presents a video system, operating in the visible spectrum range, for early smoke detection in passenger trains. The main idea is integrating standard smoke sensors with the results of a smoke detection processing, which exploits video surveillance cameras already available on-board the train. To this aim a novel video processing flow is proposed exploiting temporal, spatial and chromatic characteristics of the reference scenario. The proposed algorithm has been successfully verified with several video set and its implementation complexity fully characterized.

Although High Dynamic Range (HDR) imaging has represented, in the recent years, the topic of important researches, it has not reached yet an excellent level of the HDR scenes ac quisition using the available co mponents. Indeed, many solu-tions have been proposed ranging from bracketing to the beamsp litter but none of these solutions is really consistent with the moving scenes representing light’s level difference. In this paper, we present an optical architecture, which exploits the stereoscopic cameras, ensuring the simultaneous capture of four different ex posures of the same image on four sensors with efficient use of the available light. We also present a short description of the implemented fusion algorithm implemented. Keywords : Stereoscopic cameras, beamsplitters, APEX , HDR Imaging, Cameras architecture, AMP 1. Introduction The extensive development of computer tools is in effervescen ce year by year. It remains on e of the emerging techniques introduced in numerous applications such as quality control, medicine, and video surveillance. The artificial vision tech-niques are adapted to the envisaged applica tions and to the associated constraints. Along with this, the researches in the field of HDR images’ are constantly evolving. Indeed, the process of capturing HDR images has been the work subject of many researchers and hundreds of artists and photographers. As a result, there are many articles and patents describing methods and systems for capturing HDR images. The easiest way to HDR imag-ing involves taking a series of pictures with different exposure times [1, 2]. A lthough this method works well for static scenes, it is unfortunately not well suited for video because of different exposure times for each image, which result in varying amounts of motion blur and other effects occurring after the time of use. However, researchers have extended this approach to video capturing with alternating bright and dark exhibitions [3, 4]. In our case, we will use the stereoscopic technology to generate High Dynamic Range (HDR) images. In order to achieve that, we require three to five images with different exposures. With the combination between two lenses of a camera and a beam splitter, we can get up to four differen t images. Thus, we will study the necessary diaphragm opening allowing us to get the best exposures and define the architecture that we would deploy. The paper will be organized as follow. In the section II, we will discuss about the researches related to stereoscopic cameras and HDR images. Then, Section III will detail the proposed architectur e, the criteria to be met and the results that are expected to get. Finally, th is article will finish by a conclusion and an introduction of some perspectives.

In this paper, the ultra-high speed (UHS) video capturing results of time dependent dielectric breakdown (TDDB) of MOS capacitors using the UHS camera with the maximum frame rate of 10M frame per second (fps) are reported. In order to capture the breakdown, we set a trigger circuit which detects the rapid current increase through the MOS capacitor. Some movies have succeeded to capture the intermittent light emissions on some points of the gate during the breakdown. From the movies taken at 100K to 1M fps, the distribution centers of the light emission time and the period were 10 sec and 30 μsec, respectively. From the movies taken at 10M fps, the light emission time and the period were less than 10 μsec. The random failure mode has higher percentage of single light emissions than that of the wear-out failure mode, indicating a correlation between of the light emission mode and the TDDB failure mode.

Videos can be taken with nearly every camera, digital point and shoot cameras, DSLRs as well as smartphones and more and more with so-called action cameras mounted on sports devices. The implementation of videos while generating QR codes and relevant pictures out of the video stream via a software implementation was contents in last years’ paper. This year we present first data about what contents is displayed and how the users represent their videos in printed products, e.g. CEWE PHOTOBOOKS and greeting cards. We report the share of the different video formats used, the number of images extracted out of the video in order to represent the video, the positions in the book and different design strategies compared to regular books.

In order to overcome image shakes in the video of the camera mounted on a movable platform and to implement the image stabilization in real-time, a FPGA platform of real-time digital image stabilization (DIS) based on bit-plane matching was realized. Firstly, the local motion vectors were estimated by using Gray Code bit-plane matching. Then, the global motion vector was generated with a median filter method. Following that, a low pass filter was applied on the previous global motion vectors to get the current motion compensation vector. At last, the stabilized video was obtained by compensation the original one. A multi-bits concurrent matching method was used when estimating the local motion vectors using the bit-plane, which increased the parallelism of the FPGA and speeded up the matching velocity. The FPGA implementation of the function modules of video capture control, image buffering, motion estimation, motion filtering, and motion compensation were detailed out. The experiment results indicate that the proposed method can stabilize the 25 fps video with 720x576 pixels in real-time, and can be applied in real-time applications. 2014 Copyright SPIE.

Automatic video identification is important for indexing, search purposes, and removing illegal material on the Internet. By combining a high-speed correlation engine and web-scanning technology, we developed the Fast Recognition Correlation system (FReCs), a video identification system for the Internet. FReCs is an application thatsearches through a number of websites with user-generated content (UGC) and detects video content that violates copyright law. In this paper, we describe the FReCs configuration and an approach to investigating UGC websites using FReCs. The paper also illustrates the combination of FReCs with an optical correlation system, which is capable of easily replacing a digital authorization sever in FReCs with optical correlation.

An apparatus comprises a processor configured to: process, automatically and in real time, segmentation of a video object from a portion of a video, wherein the video object is a foreground of the video, and wherein a remaining portion of the video is a background of the video; and remove the background.

The video output of thermal imagers stayed constant over almost two decades. When the famous Common Modules were employed a thermal image at first was presented to the observer in the eye piece only. In the early 1990s TV cameras were attached and the standard output was CCIR. In the civil camera market output standards changed to digital formats a decade ago with digital video streaming being nowadays state-of-the-art. The reasons why the output technique in the thermal world stayed unchanged over such a long time are: the very conservative view of the military community, long planning and turn-around times of programs and a slower growth of pixel number of TIs in comparison to consumer cameras. With megapixel detectors the CCIR output format is not sufficient any longer. The paper discusses the state-of-the-art compression and streaming solutions for TIs.

In recent years, in order to reduce semantic gap which exists between high-level semantics and low-level features of video when the human understanding image or video, people mostly try the method of video annotation where in signal’s downstream, namely further (again) attach labels to the content in video-database. Few people focus on the idea that: Use limited interaction and the means of comprehensive segmentation (including optical technologies) from the front-end of collection of video information (i.e. video camera), with video semantics analysis technology and corresponding concepts sets (i.e. ontology) which belong in a certain domain, as well as story shooting script and the task description of scene shooting etc; Apply different-level semantic descriptions to enrich the attributes of video object and the attributes of image region, then forms a new video model which is based on Video Object Plan (VOP) Coding. This model has potential intellectualized features, and carries a large amount of metadata, and embedded intermediate-level semantic concept into every object. This paper focuses on the latter, and presents a framework of a new video model. At present, this new video model is temporarily named “Video Model of Semantic-Preloaded or Semantic-Preload Video Model (simplified into VMoSP or SPVM)”. This model mainly researches how to add labeling to video objects and image regions in real time, here video object and image region are usually used intermediate semantic labeling, and this work is placed on signal’s upstream (i.e. video capture production stage). Because of the research needs, this paper also tries to analyses the hierarchic structure of video, and divides the hierarchic structure into nine hierarchy semantic levels, of course, this nine hierarchy only involved in video production process. In addition, the paper also point out that here semantic level tagging work (i.e. semantic preloading) only refers to the four middle-level semantic. All in all, this research was unfolded is based on analyzed the characteristic of the existing video mode, and with reference to MPEG series standard.

Compared with the traditional infrared imaging technology, the new type of optical-readout uncooled infrared imaging technology based on MEMS has many advantages, such as low cost, small size, producing simple. In addition, the theory proves that the technology’s high thermal detection sensitivity. So it has a very broad application prospects in the field of high performance infrared detection. The paper mainly focuses on an image capturing and processing system in the new type of optical-readout uncooled infrared imaging technology based on MEMS. The image capturing and processing system consists of software and hardware. We build our image processing core hardware platform based on TI’s high performance DSP chip which is the TMS320DM642, and then design our image capturing board based on the MT9P031. MT9P031 is Micron’s company high frame rate, low power consumption CMOS chip. Last we use Intel’s company network transceiver devices-LXT971A to design the network output board. The software system is built on the real-time operating system DSP/BIOS. We design our video capture driver program based on TI's class–mini driver and network output program based on the NDK kit for image capturing and processing and transmitting. The experiment shows that the system has the advantages of high capturing resolution and fast processing speed. The speed of the network transmission is up to 100Mbps.

The cables in anchorage zone of cable-stayed bridge are hidden within the embedded pipe, which leads to the difficulty for detecting the damage of the cables with visual inspection. We have built a detection device based on high-resolution video capture, realized the distance observing of invisible segment of stay cable and damage detection of outer surface of cable in the small volume. The system mainly consists of optical stents and precision mechanical support device, optical imaging system, lighting source, drived motor control and IP camera video capture system. The principal innovations of the device are ⑴A set of telescope objectives with three different focal lengths are designed and used in different distances of the monitors by means of converter. ⑵Lens system is far separated with lighting system, so that the imaging optical path could effectively avoid the harsh environment which would be in the invisible part of cables. The practice shows that the device not only can collect the clear surveillance video images of outer surface of cable effectively, but also has a broad application prospect in security warning of prestressed structures.

Digital video products such as TVs, set-up boxes and DV players have circuits that enhance quality of incoming video content. User may control parameters of these circuits according to video source for optimum quality. However, there is a need for a procedure that can adjust these parameters automatically without user interaction. A three stages method for content adaptive enhancement of video images (CAEVI) in display processors is proposed. The first stage measures video signal statistics such as intensity and frequency histograms over image’s active area. The following stage generates control parameters for image processing blocks after measured statistics analysis. One of four quality classes (low, medium, high or special) is assigned to the incoming video, and a set of predefined control parameters for this class is selected. At the third stage, the set of control parameters is applied to the corresponding image processing blocks to reduce noise, improve signal transitions, enhance spatial details, contrast, brightness and saturation, and resample the video image. Video signal statistics are measured and accumulated for each frame, and control parameters are gradually adjusted on scene basis. Measuring and processing blocks are implemented in hardware to provide real time response. Image analysis and quality classification algorithm is implemented in embedded software for flexibility. The proposed method has been implemented in video processor as “Auto HQV” feature. The method was originally developed for TVs and. It is currently under adaptation for hand held devices.

Today, video cameras connected to frame grabbers or video capture cards (VCCs) are used in many applications such as traffic control, surveillance, medical systems or machine vision. In this work, we present a method for determining the spatial-frequency response of VCCs. This method is based on the modulation transfer function (MTF) determination from speckle patterns using a low-cost experimental setup. We have evaluated and compared three different VCCs. The three VCCs produce an amplification (boost) in the horizontal MTF in a different spatial-frequency range, also differing in the maximum amplification value

We introduce Salience-Based Compression (SBC), a vision-guided pre-filtering technology, coupled with standardsbased video coding. SBC works by detecting and tracking salient features and keeping them sharp; non-salient features are lowpass filtered, causing an automatic and beneficial drop in bit rate. Because salience-based pre-filtering is performed as a pre-processing step, it can interface to any COTS video encoder, thus enabling use in existing infrastructures and ensuring the compliance of the video bitstream that is produced. For typical aerial surveillance video, SBC can reduce bit rate by up to a factor of four, yet still provide full motion video (FMV) and preserve salient visual information.

Advances in 3D scanning have enabled the real-time capture of high-resolution 3D video. With these advances comes the challenge of streaming and storing this 3D video in a manner that can be quickly and effectively used. To do this, different approaches have been taken, a popular one being image based encoding, which projects from 3D into 2D, uses 2D compression techniques, and then decodes from 2D back to 3D. One such technique that does this is the Holovideo technique, which has been shown to yield great compression ratios. However, the technique was originally designed for the RGB color space and until recently could not be used with codecs that use the YUV color space such as the H.264 codec. This paper addresses this issue, generalizing Holovideo to the YUV color space, allowing it to leverage the H.264 codec. Compression ratios of over 352 : 1 have been achieved when comparing it to the OBJ file format, with mean squared error as low as .204% making it a viable solution for 3D video compression.

The article put forward a method which had been used for video image acquisition and processing, and a system based on Java media framework (JMF) had been implemented by it. The method could be achieved not only by B/S mode but also by C/S mode taking advantage of the predominance of the Java language. Some key issues such as locating video data source, playing video, video image acquisition and processing and so on had been expatiated in detail. The operation results of the system show that this method is fully compatible with common video capture device. At the same time the system possesses many excellences as lower cost, more powerful, easier to develop and cross-platform etc. Finally the application prospect of the method which is based on java and JMF is pointed out.

In order to make a large amount of video data compression and effectively with limited network bandwidth to transfer smoothly, this article using the MPEG-4 compression technology to compress video stream. In the network transmission, according to the characteristics of video stream, for transmission technology to carry out full analysis and optimization, and combining current network bandwidth status and protocol, to establish one network model with transferring and playback video streaming effectively. Through a combination of these two areas, significantly improved compression and storage of video files and network transmission efficiency, increased video processing power.

With video detection technology as the core,this paper designed and implemented vehicle detection and identification in intelligent transportation system.The hardware design consisted of video capture module,video transmission module and image processing module;The software design primarily included motion detection,shadow segmentation,edge detection, feature extraction and vehicle classification.In the vehicle detection and identification algorithm,applied fusion concept and attempted to design a linear classifier with perceptive gradient descent method to identify vehicles.The experimental results validated that the methods used in this paper obtained good effect,and got a high recognition rate.

Image distribution is getting more and more processor demanding, due to the increased quality requirements and the need for real time imaging. Therefore, improv ed techniques and processo rs are being designed. Another attractive approach is keeping image processing in the optical domain and extending, as much as it is possible, the functionalities performed to this domain. Optical processing is a reality in many research fields, namely optical communications. Results reported in literature show that it is possible to exploit optical components to accomplish image capture, optical transform processing, sampling and threshol ding. We propose a general architecture for all-optical image acquisition, processing and transmitting, and re view potential best fit for each functionality. Keywords: All-optical processing, optical transforms, data compression, image/video processing. 1. INTRODUCTION At present, digital video or image delivery is one central researc h topic, since the technology is now mature to provide a concrete prospective of progress in this field, and also the interest on video streaming is clearly growing, from both services provider and users. Optical fiber networks are already used for image/video distribution, but photonic technologies can be exploited to accomplish not just delivery, but processing functionalities as well. This approach allows keeping image in the optical domain, with the first relevant achievement of overcomi ng the limitations due to Optical-to-Electrical-to-Optical (OEO) stages. In this framework, the main aim of the CITO (Image Co mpression using Optical Transforms ) project is to evaluate the potential of optical technologies in meeting the high processing requirements of actual and emerging image and video formats, and in overcoming limitation imposed by electronic based architecture, such as latency and power consumption. Therefore, with this work we aim to present a general architecture, for all-optical image/video acquisition, processing and transmitting. Proposed system architectu re is based on the following main fu nctionalities: video capture, transform, quantization, coding and transmission. A review of some of the potential best solutions and technologies for the implementation of such functionalities is presented, and the main challenges are investigated. To the best of our knowledge, the potential of integrated optics in the field of all optical video/image processing system is still not well exploited, especially from the integration point of view. Thus, the subject deserves major investigations and motivates our objectives.

A compact low-cost LWIR test station has been developed that provides real time MTF testing of IR optical systems and EO imaging systems. The test station is intended to be operated by a technician and can be used to measure the focal length, blur spot size, distortion, and other metrics of system performance. The challenges and tradeoffs incorporated into this instrumentation will be presented. The test station performs the measurement of an IR lens or optical system's first order quantities (focal length, back focal length) including on and off-axis imaging performance (e.g., MTF, resolution, spot size) under actual test conditions to enable the simulation of their actual use. Also described is the method of attaining the needed accuracies so that derived calculations like focal length (EFL = image shift/tan(theta)) can be performed to the requisite accuracy. The station incorporates a patented video capture technology and measures MTF and blur characteristics using newly available lowcost LWIR cameras. This allows real time determination of the optical system performance enabling faster measurements, higher throughput and lower cost results than scanning systems. Multiple spectral filters are also accommodated within the test stations which facilitate performance evaluation under various spectral conditions.

We have already developed glasses-free three-dimensional (3-D) displays using multi-projectors and a special diffuser screen that results in a highly realistic communication system. The system can display 70-200 inch large-sized 3-D images with full high-definition video image quality. The displayed 3-D images were, however, only computergenerated graphics or still images of actual objects. In this work, we studied a 3-D video capturing method for our multiprojection 3-D display. We analyzed the optimal arrangement of cameras for the display, and the image quality as influenced by calibration error. In the experiments, we developed a prototype multi-camera system using 30 highdefinition video cameras. The captured images were corrected via image processing optimized for the display. We successfully captured and displayed, for the first time, 3-D video of actual moving objects in our glasses-free 3-D video system.

Bronchoscopes contain wide-angle lenses that produce a large field of view but suffer from radial distortion. For image-guided bronchoscopy, geometric calibration including distortion correction is essential for comparing video images to renderings developed from 3D computed-tomography (CT) images. This paper describes an easy-to-use system for bronchoscopic video-distortion correction and studies the robustness of the resulting calibration over a wide range of conditions. The internal calibration method integrated into the system incorporates a well-known camera calibration framework devised for general camera-distortion correction. The robustness study considers the calibration results as follows: (1) varying lighting during video capture, (2) using different number of captured images for parameter estimation, (3) changing camera pose with respect to the calibration pattern, (4) recording temporal changes in estimated parameters, and (5) comparing parameters between different bronchoscopes of a same model. Multiple bronchoscopes were successfully calibrated under a variety of conditions.

In the stereoscopic frame-compatible format, the separate high-definition left and high-definition right views are reduced in resolution and packed to fit within the same video frame as a conventional two-dimensional high-definition signal. This format has been suggested for 3DTV since it does not require additional transmission bandwidth and entails only small changes to the existing broadcasting infrastructure. In some instances, the frame-compatible format might be used to deliver both 2D and 3D services, e.g., for over-the-air television services. In those cases, the video quality of the 2D service is bound to decrease since the 2D signal will have to be generated by up-converting one of the two views. In this study, we investigated such loss by measuring the perceptual image quality of 1080i and 720p up-converted video as compared to that of full resolution original 2D video. The video was encoded with either a MPEG-2 or a H.264/AVC codec at different bit rates and presented for viewing with either no polarized glasses (2D viewing mode) or with polarized glasses (3D viewing mode). The results confirmed a loss of video quality of the 2D video up-converted material. The loss due to the sampling processes inherent to the frame-compatible format was rather small for both 1080i and 720p video formats; the loss became more substantial with encoding, particularly for MPEG-2 encoding. The 3D viewing mode provided higher quality ratings, possibly because the visibility of the degradations was reduced.

3D film and 3D TV are becoming reality. More facilities and devices are now 3D capable. Compared to capture 3D video content directly, 2D to 3D video conversion is a low-cost, backward compatible alternate. There also exists a tremendous amount of monoscopic 2D video content that are of high interest to be displayed on 3D devices with noticeable immersiveness. 2D to 3D video conversion, therefore, has drawn lots of attention recently. In this paper, a low complexity 2D to 3D conversion algorithm is presented. The conversion generates stereo video pairs by 3D warping based on estimated per-pixel depth maps. The depth maps are estimated jointly by motion and color cues. Subjective tests show that the proposed algorithm achieves 3D perception with acceptable artifact.

Distributed Video Coding (DVC) is an emerging video coding paradigm for the systems that require encoders having low complexity that are supported by decoders having high complexity as would be required for, say, real-time video capture and streaming from one mobile phone to display on another. Under the assumption of an error-free transmission channel, the coding efficiency of current DVC systems is still below that of the latest conventional video codecs, such as H.264/AVC. To increase coding efficiency we propose in this paper that either every second Key frame or every Wyner-Ziv frame is downsampled by a factor of two in both dimensions prior to encoding and subsequent transmission. However, this would necessitate upsampling coupled with interpolation at the decoder. Simple interpolation (e.g., bilinear or FIR filter) would not suffice since high-frequency (HF) spatial image content would be missing. Instead, we propose the incorporation of a super-resolution (SR) technique that is based upon using example High Resolution images with content that are specific to the Low Resolution scene that needs its HF content to be recovered. The example-based scene-specific SR technique will add computational complexity to the decoder side of the DVC system, which is allowable within the DVC framework. Rate-distortion curves will show that this novel combination of SR with DVC improves the system performance by up to several decibels as measured by the PSNR, and can actually exceed the performance of an H.264/AVC codec, using GOP=IP, for some video sequences.

In this work, a novel method for color video compression using key-frame based color transfer has been proposed. In this scheme, compression is achieved by discarding the color information of all but few selected frames. These selected frames are either the key frames (frame selected by a key frame selection algorithm) or the Intra coded (I) frames. The partially colored video is compressed using a standard encoder thereby achieving higher compression. In the proposed decoder, a standard decoder first generates the partially colored video sequence from the compressed input. A color transfer algorithm is then used for generating the fully colored video sequence. The complexity of the proposed decoder is close to a standard decoder, allowing its use in wide variety of applications like video broadcasting, video streaming, hand-held devices etc.

The fabric quality defect detection is very useful for improving the qualities of the products. It is also very important to increase the reputation and the economic benefits of a company. However, there are some shortcomings in the traditional manual detection methods, such as the low detection efficiency, the fatigue problem of the operator, and the detection inaccuracy, etc. The existing 2D image processing methods are difficult to solve the interference which is caused by non-defect case, just like the cloth folds, the flying thick silk floss, the noise from the background light and ambient light, etc. In order to solve those problem, the BCCSL (Binocular Camera Color Structure Light) method and SFMS (Shape from Multi Shading) method is proposed in this paper. The three-dimensional color coordinates of the fabric can be quickly and highly-precision obtained, thus to judge the defects shape and location. The BCCSL method and SFMS method can quickly obtain the three-dimensional coordinates' information of the fabric defects. The BCCSL method collects the 3D skeleton's information of a fabric image through the binocular video capture device and the color structured light projection device in real-time. And the details 3D coordinates of fabric outside strip structural are obtained through the proposed method SFMS. The interference information, such as the cloth fold, the flying thick silk floss, and the noise from the background light and ambient light can be excluded by using the three-dimensional defect identification. What is more, according to the characteristics of 3D structure of the defect, the fabric can be identified and classified. Further more, the possible problems from the production line can be summarized.

This paper first briefly reviewed sources of visual quality degradation during video compression and also different video quality assessment techniques. It further extended discussion beyond video compression to other modules in different video application pipeline. Different video application is composed by different processing modules, such as sensor, video encoder, and display. Visual experience is not always determined by single module. Hence, the way of quantifying visual experience on different video applications should vary accordingly. Furthermore, users have very different expectation on visual experience in each application. Different quality assessment approach should be adopted based on various users' expectation.

Distributed simulation environments are increasingly using video to stimulate operational systems and their prototypical equivalents. Traditionally, this video has been synthesized and delivered by an analog means to consuming software applications. Scene generators typically render to commodity video cards, generate out of band metadata, and convert their outputs to formats compatible with the stimulated systems. However, the approach becomes hardware intensive as environment scale and distribution requirements grow. Streaming video technologies can be applied to uncouple video sources from their consumers, thereby enabling video channel quantities beyond rendering hardware outputs. Moreover, metadata describing the video content can be multiplexed, thereby ensuring temporal registration between video and its attribution. As an application of this approach, the Night Vision Image Generator (NVIG) has been extended and integrated with distribution architectures to deliver streaming video in virtual simulation environments. Video capture hardware emulation and application frame buffer reads are considered for capturing rendered scenes. Video source to encoder bindings and content multiplexing are realized by combining third party video codec, container, and transport implementations with original metadata encoders. Readily available commercial and open source solutions are utilized for content distribution and demultiplexing to a variety of formats and clients. Connected and connectionless distribution approaches are discussed with respect to latency and reliability. Client side scalability, latency, and initialization issues are addressed. Finally, the solution is applied to tactical systems stimulus and training, showing the evolvement from the analog to the streamed video approach.

Degraded visual conditions can marvel the curious and destroy the unprepared. While navigation instruments are trustworthy companions, true visual reference remains king of the hills. Poor visibility may be overcome via imaging sensors such as low light level charge-coupled-device, infrared, and millimeter wave radar. Enhanced Vision systems combine this imagery into a comprehensive situation awareness display, presented to the pilot as reference imagery on a cockpit display, or as world-conformal imagery on head-up or head-mounted displays. This paper demonstrates that Enhanced Vision imaging can be achieved at video rates using typical CPU / GPU architecture, standard video capture hardware, dynamic non-linear ray tracing algorithms, efficient image transfer methods, and simple OpenGL rendering techniques.

Monitoring video data sources received from UAVs is especially challenging because of the quality of the video received. Due to the individual characteristics of the unmanned platform and the changing environment, the important elements in the scene are not always observable or easily identified. In addition to typical sensor noise, significant image degradation can occur during transmission of the video from an airborne platform. Interference from other transmitters, analog noise in the embedded avionics, and multi-path effects can corrupt the video signal during transmission, introducing distortion in the video received at the ground. In some cases, the loss of signal is so severe; no information is received in portions of an image frame. To improve the corrupt video, we capitalize on the oversampling in the temporal domain (across video frames), applying a data fusion approach to de-noise the video. The resulting video retains the significant scene content and dynamics, without distracting artifacts from noise. This allows humans to easily ingest the information from the video, and make it possible to utilize further video exploitation algorithms such as object detection and tracking.

Distributed Video Coding (DVC) is an emerging video coding paradigm for the systems that require low complexity encoders supported by high complexity decoders. A typical real world application for a DVC system is mobile phones with video capture hardware that have a limited encoding capability supported by base-stations with a high decoding capability. Generally speaking, a DVC system operates by dividing a source image sequence into two streams, key frames and Wyner-Ziv (W) frames, with the key frames being used to represent the source plus an approximation to the W frames called S frames (where S stands for side information), while the W frames are used to correct the bit errors in the S frames. This paper presents an effective algorithm to reduce the bit errors in the side information of a DVC system. The algorithm is based on the maximum likelihood estimation to help predict future bits to be decoded. The reduction in bit errors in turn reduces the number of parity bits needed for error correction. Thus, a higher coding efficiency is achieved since fewer parity bits need to be transmitted from the encoder to the decoder. The algorithm is called inter-bit prediction because it predicts the bit-plane to be decoded from previously decoded bit-planes, one bitplane at a time, starting from the most significant bit-plane. Results provided from experiments using real-world image sequences show that the inter-bit prediction algorithm does indeed reduce the bit rate by up to 13% for our test sequences. This bit rate reduction corresponds to a PSNR gain of about 1.6 dB for the W frames.

Today, 3D viewing devices still need qualitative content; up to now, there is no real 3D video shooting system specifically designed to ensure a qualitative 3D experience on some pre-chosen 3D display. A fundamental element of multiscopic image production is the geometrical analysis of shooting and viewing conditions in order to obtain a qualitative 3D perception experience. Many autostereoscopic camera systems are proposed but none is designed with control of possible depth distortions in mind. This article introduces a patented autostereoscopic camera design scheme based upon this distortion control. Thanks to our scientific know-how, we based our work on the link between the shooting and rendering geometries, which enables to control the distortion of the perceived depth. Thus this design scheme provides camera systems producing qualitative 3D content complying with any pre-chosen distortion when rendered on any specific autostereoscopic display. Thanks to our technological expertise, we use this design scheme to product pre-industrial camera systems devoted to 3D live or pre-recorded shooting. These systems are compact, lightweight, easy to deploy and rather adaptable to other conditions (3D displays, depth distortion). We will introduce the associated software, which allows to control our 3D cameras and to display in real-time on the autostereoscopic display formerly specified. According to numerous spectators, both naive and expert, the 3D perception is really qualitative.

Thanks to the development of network, video devices are used in various aspects of our lives such as video conference, video call, etc. It is, however, very common that people tend to look at the computer screen instead of the video capture device, which can affect the communication. We present a novel approach to solve this problem. Through estimating the divert head angle and eyeball location recognition, we can estimate the visual angle. By moving the eyeball to adjust visual line, it looks like that we're looking at each other. Our work is on the basis of face alignment and there is a geometric 3D model and novel R -α, K -β relationship analysis methods adopted in this paper.

A novel dual module remote video monitoring system is designed and realized in this paper, which is based on TDSCDMA and CDMA 2000 1X wireless networks. The key technologies of designing and realization are presented in detail. In addition, test results show that the proposed system efficiently uses wireless channel resources and improves transmission rate. Compared to traditional single module video monitoring system, our designed system can provide a better performance in real-time property and stability.