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The color reproduction is based on visual perception. The psychophysics experiments present the light source; illuminants and view background affect the results of color matching. Paper is a typical substrate for printed color matching and effects printed color greatly. Now almost all of print papers contain optical brightening agents, which changes significantly the color appearance of printed color and makes color shifting of printed color matching. This paper used CAT02 chromatic adaptation models to transform the measurements of printed color in paper with and without OBA, compared the effect of printed color matching between before and after transforming with display, present the method using chromatic adaptation transforms to improve the accurate of printed color matching.

Much progress has been made in the field of digital imaging technology with the widespread use of CMOS and CCD devices and the high computing power of IC chips. However, there still are many technological problems to overcome to achieve lightweight and affordable high density 3D lossless imaging for both industrial and scientific applications. This paper will focus on the latest development of freeform optical technology and powerful image analysis techniques to develop a compound eye camera system so as to extract the 3D relative position coordinates of the sub-object in the field of view, and to compensate the shadow effect in the images caused by the non-uniform illumination to obtain high quality lossless images. Such a novel compound eye system will find applications in delivering 3D image of digital camera, increasing capability of scientific profiling measuring instrument, and lowering cost and enhancing resolution of wide-field, video-rate, gigapixel cameras such as the AWARE designed by Duke University.The main objective of this paper is to design a novel compound eye system from high definition 3D lossless digital imaging technology to achieve the realistic three-dimensional positional information of the object in both near and far fields. In the imaging process, the ultimate imaging quality is affected and limited by the resolution of the detector, the field of view, wavefront aberration, resolution of the optical imaging system and the ambient light.The novel compound eye imaging system includes two modules: one is the optical imaging module with compound eye optical elements with other secondary optical lenses, while the other one is the image analysis module. By combining the above optical hardware with the image analysis software, the relative position information of the sub-objects in the picture and the lighting condition of the environment can be deduced accurately.

It is important to obtain the 3d coordinate in the field of measuring. How accurate, fast, convenient to obtain the 3d coordinate affects the accuracy and reliability of measurement directly. Through studying the basic theories of machine vision this paper focus on the study of a stereo vision measurement model based on the intersecting axis. In view of the parameters in the model of binocular stereo vision, this paper uses the Zhang Zhengyou calibration method to calibrate the system of Stereo vision. In order to test the accuracy of the system, this paper measures the distance of two standard circular. Finally, the machining experiment validates the proposed method.

This paper analysis the characteristics of High Spatial Resolution Remote Sensing Image (HSRRSI), consider the drawback of pixel-wise Classification, an Object-based method was taken to classify the image. The paper firstly preprocess and coarsely segment the image, secondly optimize the segmented results for deeply processing, then extracting the image feature from the original image and segmented results, finally classify the image and assess the results.

The paper analysis mean filter, median filter and morphology filter. The paper studied order morphology theory and its filter character. Based on this, the paper proposed multi-scale and multi-structure filter algorithm based on order morphology. The result of simulation shows that the algorithm can not only keep the edge and detail of medical image but also can enhance the contrast of recovery image.

Stereo matching methods are widely used in computer vision and stereo reconstruction, from the perspective of improving the matching accuracy, this paper focuses on the global optimization algorithm. An improved Belief Propagation method is proposed in this paper, by involving more pixels into information transmission, our method improves the accuracy ofstereo matching. The experimental results verify the efficiencyand reliability of our method.

In this paper ,a color printing defect automatic online detection method based on digital image processing technique is proposed. The main idea of this method is comparison of defect product and template and it makes up of following key models. Firstly, multi-scale segmentation is applied to composed image which is overlaid by detecting product and template image. Secondly, an automatic region similarity analysis calculation is taken to segmentation obtained in multi-scale segmentation. The color difference between detecting product and template can be calculated accurately. Thirdly, defect detection results can be obtained according to threshold segmentation. Finally, the characteristics and advantages are approved by experimental analysis and discussion. Algorithm parameters are adjusted and modified to improve the stability and effectiveness. Experimental results approve that color printing defect automatic detection method in this paper has the characteristics of effectiveness and applicability. And experimental results indicate that this method has the advantage of judging the defect types automatically.

Synthetic Aperture Radar (SAR) has become one of the important means for the ocean remote sensing detection of oil spills. The existing SAR image segmentation method has the issues of edge blur, poor contrast, non-uniform intensity image, so the segmentation effect is not ideal. This paper presents a variational level set SAR image of oil spill detection method based on fuzzy clustering. First of all, apply the threshold method on initial segmentation of the original SAR image to transform the initial segmented image as fuzzy clustering. Secondly, introduce the clustering results into the initial level set function to achieve the initial contour. Finally, add fuzzy clustering model in the level set energy function to complete the level set evolution process and get the final segmented image. This paper uses the threshold segmentation results to achieve the initialization of the variational level set function profile. In theory, it could improve the level set method for efficiency, and reduce the wrong segmentation phenomenon. The experimental results show that the SAR image segmentation method of oil spill has good segmentation qualities and is suitable for the edge complex image segmentation.

With the improvement of computer hardware and software performance, digital multimedia technology has been applied to various fields. The visual effect of ceramic art image is affected mainly by the brightness, texture and color, in which the image defects will affect the visual effect of the ceramic product. This paper designs the digital processing system of a new ceramic art image processing, the system can repair defects in ceramic art image. In order to verify the validity and reliability of digital processing system, the lead-free perovskite structure BZT based ceramics is prepared in this paper, and the use of electron microscope and digital camera take the ceramic products processing image with artistic defects, and then using VB programming digital image processing technology carries out color re coating for the ceramic, the ceramic products electron microscopy images after restoration will be obtained by the image boundary restructuring, which provides a new computer method for the processing art of the ceramic products.

With the development of computer graphics, real-time rendering-based VF: technology has been applied in more and more fields. LOD is the key technology in large-scale terrain rendering. In this paper, the basic concept of LOD is introduced briefly and some algorithms of LOD in use are mentioned and analyzed; secondly as one of algorithms of LOD, View-Dependent Progressive Mesh algorithm is studied and improved, the result of implementing the large-scale terrain’s LOD by using VDPM is presented. There are key technologies in LOD Large-scale terrain real-time rendering are researched. Relative technologies are presented such as: LOD of the terrain, visibility culling, and cracks eliminate, view-dependent refine, LOD error, technologies of texture etc. Using LOD technology, VR system can greatly reduce the; number of polygons produced in real-time rendering procedure. Finally, we do experimental design work based on the methods and techniques presented by this paper.

This paper aims at the difficulty that lack of observation model and high-dimensional sampling in video tooning, proposes a method based on key frame matching and dual-directional Markov chain Monte Carlo sampling of video motion redirection. At first, after extracting the key frame of a given video, By affine transformation and linear superposition, the subject initializes the video’s space-time parameters and forms the observation model; Secondly, in each space-time, based on the bi-directional Markov property of each frame, This paper proposed a dual-directional Markov chain Monte Carlo sampling particle filter structure and takes full advantage of the relationship of the front and back frame of the parameters to estimate motion redirection parameters. At the same time, for high-dimensional sampling problem, the subject according to the directional parameters’ correlation implements classification of skeleton parameters-morphological parameters-physical parameters, proposes a hierarchical genetic strategy to optimize the output parameters and improves the efficiency of the algorithm. The research of this paper will produce an efficient and prominent animation expressive video motion redirection method and play an important role on video animation of the development.

This paper presents a 3D gesture recognition technology based on machine vision as the center. Based on a large number of experiments, this paper sums up and introduces the existing gesture recognition technology, the key research contents of gesture recognition, as well as the history of development of gesture recognition technology. Then, the paper does research in the main technology of gesture recognition .The experimental results show that the method can realize 3D gesture recognition in video sequences with real-time and stability, even more; it can get better recognition result.

In this paper, frame differential method will be used to detect moving targets in a static background video file, and pre-contour can be obtained by binarizing the detected targets . However,, the result are not what was expected, so the expansion and corrosion of mathematical morphology are used to extract the final contour of moving targets. in the progress of dealing with massive data , mathematical morphology is not good enough to achieve the need of the real-time in video surveillance. Considering the dilation and erosion is a kind of parallel processing operations, in order to improve the speed of mathematical morphology operations, this paper offers detailed implementation process of the dilation algorithm for parallel computing on GPU. Experimental results showed that GPU parallel processing on mathematical morphology algorithm faster than the CPU serial processing.

The objective of this paper is to build a system for pedestrian detection in an outdoor environment. The contribution of this paper is the detection method that integrates the silhouette edge information with patterns of motion in each frame of the image sequence. The test results show that the high-precision, good adaptability, and real-time performance of the proposed method.

This paper first introduced the geometric correction method for remote sensing image used in the software, put forward the method precision visualization comprehensively and systematically describes the quality of remote sensing image rectification. This paper illustrates an instance method and its application through a IKONOS image rectification,and some useful conclusions are obtained. Keywords: Remote sensing image; image rectification; accuracy; spatial interpolation; error

Due to the development of image segmentation and reconstruction technology, it provides a larger space for development of the image enhancement technology. Under the promoting of the image processing calculation, the capture and recognition function of digital X-ray photography technology are stronger, and the image processing precision is higher. Based on the variation principle, this paper uses the function approximation to improve the X-ray photography image processing technology, and obtains the new boundary value reconstruction condition of X-ray photography. In order to verify the effectiveness and reliability of the mathematical model and algorithm of the boundary value reconstruction, this paper uses MATLAB software and C language to debug the algorithm, and realizes the digital color rendering for the images at the terminal of track and field, obtains the image reconstruction algorithm under different boundary values. It provides a new computer method for the research on image enhancement technology.

This paper presents an algorithm for hiding information’s in raw video steams using art of steganography using discrete wavelet transform. While mostly applied to still images in the past, it has become very popular for video streams recently. When steganographic methods are applied to digital video streams, the selection of target pixels, which are used to store the secret data, is especially crucial for an effective and successful-embedding process; if pixels are not selected carefully, undesired spatial and temporal perception problems occur in the stegno-video. Typically, an irrecoverable steganography algorithm is the algorithm that makes it hard for malicious third parties to discover how it works and how to recover the secret data out of the carrier file. In this paper, a new embedding algorithm is proposed to hide the secret data in moving videos. The 2D-DCT of the video is taken and the secret message is embedded. The performance measures are evaluated for the quality of the video after the data hiding and show good results.

Compressed sensing is referred to as the CS technology; it can realize image compression and reconstruction process in low sample rate. It has great potential to reduce the sampling rate and improve the quality of image processing. In this paper, we introduce the structure prior model into the compressed sensing and image processing, and make the image reconstruction of high dimensional optimization process simplified into a series of low dimensional optimization process, which improves the processing speed and image quality. In order to verify the effectiveness and reliability of the proposed algorithm, this paper uses combined control form of C language and MATLAB software to design the programming of structure prior model, and use the Simulink environment to debug the program. Through the calculation we get the image block and the reconstruction result. It provides the technical reference for the research on image compressed sensing technology.

A biometric identification system may be a pc application for mechanically distinctive or confirmative of an individual from a digital image or a video frame from a video supply. One in all the ways that to try and do this can be by examination designated face expression from the image and a facial information. This paper planned dynamic face recognition from near-infrared images by exploitation sparse representation classifier. Most of the prevailing datasets for facial expressions are captured in a very visible light spectrum. However, the visible light (VIS) will modify with time and placement, causing important variations in look and texture. This new framework was designed to attain strength to pose variation and occlusion and to resolve uncontrolled environmental illumination for reliable biometric identification. This paper gift a unique analysis on a dynamic facial features recognition, exploitation near-infrared (NIR) datasets and LBP(Local binary patterns) feature descriptors. It shows sensible and strong results against illumination variations by exploitation infrared imaging system.

Disparity estimation is a basic analytic method for images and video and is highly used in fields like stereo image coding, video retrieval and stereo image segmentation. This paper proposes a new disparity estimation method. In this paper, the superiority of the multi-block matching is analyzed. The new method based on the idea of block matching constructs a multi-block matching algorithm, thereby improving matching accuracy especially in the disparity discontinuous regions. A adaptive window method based on edge detect is proposed to select the best window.The experimental results based on the Middlebury stereo datasets demonstrate that our method can achieve a better performance.

The Mean-Shift algorithm has very good tracking effect when the background is in a simple; but for a complex environment, tracking effect is not very ideal. Therefore, a new gray feature modeling method is proposed in this paper. Firstly, target in the tracking window is uniformly divided into even pieces. Then the pixel gray value of each block is calculated with subtraction of certain rules. Finally, the gray value of gray difference and the whole object value fusion are fused and established the object model. The object model that established not only contains the whole gray value information, but also contains the gray value differences between regions, has a more accurate description of the target, and then distinguish target from background better. The experiment results show that: the target model using the method in this paper to track based on the Mean-Shift algorithm, has good adaptability when the target is partially occluded and has better robustness for complex background.

The traditional virtral target aiming training uses indoor large screen projection more. Recently, the system also uses the virtual reality scene as background. According to the situation, using real-time video frame as the virtual target aiming training background for the authenticity of the virtual target aiming training scene is presented in this paper. This method fully shows the maturity of modern video acquisition technology and the innovation of virtual reality scene. This paper prensents using DirectShow tools for video frame acquisition and taking the advantages of OpenFight API for the model built by military simulation modeling software MultiGen Creator development based on OpenGL development platform and completes the building of virtual target aiming training scene based on real-time three-dimensional video scene and the consistency of virtual target and scene.

Image segmentation technique was used widely for computer vision and image processing. A robust technique of image segmentation plays a crucial role in identification problem. In this paper, a nonparametric and unsupervised method of automatic threshold for segmenting image was proposed, i.e. the optimal threshold is approximated by global average gray and local average gray, and this method was compared with other methods by using standard image. The experimental results show that our method proposed in this paper is robust. In addition, an image database of road traffic marking (www.ananth.in/RoadMarkingdetection.html) is provided to do this experiment for testing our method, the results show that our method is excellent.

The paper mainly discusses the analysis method for the psychological impact of computer vision noising technology. Actually, people's psychological acceptance and corresponding memory capacity of computer vision images with lots of noise are relatively poor. The de-noising process to computer vision images can improve the clarity, thus generating passive psychological impact. Therefore, the paper proposes a spatial domain filtering algorithm-based de-noising method for computer vision. It establishes wavelet packet decomposition tree for computer vision images and de-noises accordance with the decomposing results. The experiment results show that the proposed de-noising method has passive psychological influence and improves the memory capacity of computer vision images.

UAV Video is rapidly emerging as a widely used source of imagery for many applications in recent years. This paper presents our research on the mosaic of UAV video for the purpose of harbor surveillance. First, one new framework on estimating video frame transformation with Optical flow is presented in this paper. For this new framework, fewer number of Gaussian pyramid is created for implementing for the multiresolution approach and thus, more details for optical flow computation is well kept; Second, we make a discussion on using Fourier-Mellin Transformation in image frequency domain to estimate initial motion parameter of adjacent video frames and with those initial motion parameters, small displacements for optical flow computation can be achieved; The experimental results demonstrated that the mosaic image generated from aerial video shows satisfied visual quality and its surveillance application for fast response to time-critical event, e.g., flood, is descried.

This paper researches on the detection and tracking technology of ship intrusion and remaining based on the special surveillance video scenes of sea. A ship detection and tracking method that combines the adaptive background subtraction with centroid algorithm is proposed. Compared with the method of edge orientation histogram, the method proposed in this paper shows a lower computational complexity and a better real-time performance. The experiment demonstrate that this method has a high degree of accuracy. And it makes a realization of detecting and tracking of ship intrusion and remaining within the surveillance sea.

In order to quickly and effectively segment the video scene, a multi-modality video scene segmentation algorithm with shot force competition is proposed in this paper. This method is take full account of temporal associated co-occurrence of multimodal media data, to calculate the similarity between video shot by merging the video low-level features, then go to the video scene segmentation based on the judgment method of shot competition. The authors experiments show that the video scene can be efficiently separated by the method proposed in the paper.

Remote sensing image fusion is an important branch in the field of image fusion. Remote sensing image fusion mainly researches how to use different aerial remote sensor to obtain relevant image information. In view of the present research status in this field and the full analysis of remote sensing image fusion method and wavelet transform, the paper aims at proposing the image fusion technology of combining discrete multiwavelet transform and HIS method, then the paper analyses the experimental results with the help of MATLAB. It is proved that the analysis method of wavelet has more advantages than traditional methods: Wavelet transform fusion method can keep maximized resolution and multispectral image.

Rapid and automatic extraction of pollutants is of great importance for mobile camera in real-world scenarios. In the moving process of robot, the camera is treated as dynamic background, and the pollutants on the camera are treated as static target. So as to realize the detection of static target in dynamic scene, this paper presents an automatic extraction algorithm for pollutants based on frame difference accumulation. Firstly, this algorithm can determine whether pollutants exist or not by the overall trend of gray histogram of the cumulative frame difference images. And then if existing pollutants, Otsu algorithm was adopted to adaptively calculate threshold to convert the gray image into binary image. In this paper, analysis of the important parameters of the algorithm - cumulative frame number and frame difference threshold was implemented. Moreover, feasibility of the algorithm was verified by experiments on the automatic extraction of pollutants for gun-type camera.

The quality of side information (SI) is one of the critical factors which play an important part in the compression performance of Distributed Video Coding (DVC).In this paper, we analyze the algorithm of Motion Compensation Interpolation (MCI) and propose an improving algorithm against its limitation. The algorithm proposed firstly makes each pixel has more than one motion vectors, then picks the best vector out and makes it plays the most important role in motion compensation with weighted average. Through the simulation of different frame sequences, the PSNR of the side information generated by the algorithm proposed in this paper is 0.3-0.7dB higher than that in the original algorithm.

With the development of computer and internet, how to recognize face images rapidly has become the research focus in recent years. Therefore, face recognition technology develops rapidly, and is widely applied to national counterterrorism, information security and access control. But the researchers find that face recognition only can achieve satisfactory effect under the constraint conditions. The paper proposes face recognition algorithm based on multi-resolution analysis and classification. The algorithm firstly uses wavelet transform for multi-scale wavelet decomposition on training sample, and uses the correlation coefficient between wavelet coefficients with the maximum variance as the classification distance to classify the samples and determine the central image of the images. Face recognition algorithm based on multi-resolution analysis and classification extracts some wavelet coefficients of the images, which not only achieves the purpose of dimension reduction and reduces calculated amount, but also effectively improves the speed of face recognition. The simulation experiment proves that the algorithm proposed in the paper is effective.

This paper presents a calibration procedure for a Kinect RGB-D sensor and its application to robot simultaneous localization and mapping(SLAM). The calibration procedure consists of two stages: in the first stage, the RGB image is aligned with the depth image by using the bilinear interpolation. The distorted RGB image is further corrected in the second stage. The calibrated RGB-D sensor is used as the sensing device for robot navigation in unknown environment. In SLAM tasks, the speeded-up robust features (SURF) are detected from the RGB image and used as landmarks in the environment map. The depth image could provide the stereo information of each landmark. Meanwhile, the robot estimates its own state and landmark locations by mean of the Extended Kalman filter (EKF). The EKF SLAM has been carried out in the paper and the experimental results showed that the Kinect sensors could provide the mobile robot reliable measurement information when navigating in unknown environment.

With the development of integration of three networks which combines telecommunication network, computer network and cable television network [1-2], decision support system for stereo vision is proposed. Combined with the user experience which is given a model of the influence factor in this paper of Stereo vision, the data mining model will be more comprehensive and more convincing and the decision support system for stereo vision will be more plump and more practical. This paper designs the model of the influence factor for Stereo vision user experience which makes the data mining model for Stereo vision exhibits an excellent function.

Through the analysis of present research and application situation of binocular stereo vision system, the paper indicates an opinion that the structural parameters of system are crucial to the measurement accuracy of system. This paper focuses on several parameters to discuss the effect on the measurement accuracy, such as the distance of baseline, angles between optical axis and baseline, projection angles and so on. According to measuring principle and mathematical model of binocular stereo vision system, through deriving formulas and drawing curves by means of MATLAB, the impact that different structural parameter has on measurement accuracy is analyzed. Finally, the correctness of theoretical analysis is proved by experiment and the research result is summarized.

With the development of the computer information science and technology, image Mosaic technology has been applied to various fields, which including image compression and amplification, synthesis of images and virtual scene of image design . The algorithm of image mosaic technology research is increasing. This paper analyzes the present situation and application of image mosaic technology and proposes the genetic algorithm of image mosaic technology based on computer information theory. It also constructs the image mosaic technology flow chart. This paper simulates image magnification and synthesis technology in order to prove feasibility and reliability of algorithm by the image Mosaic technology cases. This paper puts forward opinions to the deficiency of mosaic technology and provides a theoretical reference for the application and development of image mosaic technology.

A fast remote sensing scene matching method, taking airports, oil depots, harbors and so on as research objects, is proposed in this article which is based on the SR saliency detection and frequency segmentation. Saliency detection is used to determine the candidate region where the target may exist to reduce the searching range effectively. And then, frequency segmentation is used to eliminate the frequency component except the frequency of the target to reduce the redundant information, thereby saving the computation of SIFT feature extraction and matching. A variety of experiments under different interference factors are carried out in this paper. Experimental results show that the fast matching algorithm proposed in this paper can not only maintain the validity of SIFT features under the condition of rotation, scale, illumination and viewpoint changes, but also shorten the matching time largely and improve the matching efficiency, laying the foundation for further practical application.

This paper presents some techniques for constructing panoramic image stitching from sequences of images captured by cameras from different angle in garment defects detecting area. The image stitching representation associates a transformation matrix with each input image. In this paper, we formulate stitching as a multi-image matching problem, and use invariant local features to find matches between all of the images. Our method is insensitive to the ordering, orientation, scale and illumination of the input images. It is also insensitive to noise images that are not part of a panorama, and can recognise multiple panoramas in an unordered image dataset. An improved SIFT(Scale Invariant Feature Transform) algorithm was used to locate the feature points in the scanned images targeting at the problem of automatically stitching of textile images which were scanned in divided pieces. RANSAC (random sample consensus) method is proposed to to estimate image transformation parameters and to find a solution that has the best consensus with the data. Techniques for estimating and rening camera focal lengths are also presented. In order to reduce accumulated registration errors, we apply global alignment (block adjustment) to the whole sequence of images, which results in an optimally registered image stitching. A local alignment technique is also developed which warps each image based on the results of pairwise local image registrations to compensate for small amounts of motion parallax introduced by translations of the camera and other unmodeled distortions.

In realistic image processing, it is a problem of image foreground extraction. For a large number of color image processing, an important requirement is the automation of the extraction process. In this paper, by automatically setting foreground seed, we improve the image existing segmentation algorithm; by automatically searching image segmentation region, we accomplish image segmentation with the GrabCut algorithm, which is based on Gaussian Mixture Model and boundary computing. The improved algorithm in this paper can achieve the automation of image segmentation, without user participation in the implementation process, at the same time, it improves the efficiency of image segmentation, and gets a good result of image segmentation in complex background.

Due to effects of the light by water and other particles, the quality of underwater image will degrade. The traditional underwater image segmentation methods based on intensity and spectrum have difficulty in determining boundary. Inspired by the visual system of mantis shrimps, this paper constructed a feedback neural network model, in which the parameters were optimized using machine learning method. Based on this model, we combine the polarization and intensity information to achieve the underwater polarization image segmentation. The results of experiment prove that the neural network model designed in this paper can improve the accuracy of underwater image segmentation.

As the number of students who attend the arts exams has been growing, each admission institutions need to score the human head portraits of art sketch with the number of ten thousand and even 100 thousand. Thus it is an innovative research on how to conduct image recognition with the help of advanced computer technology. Image Recognition Technology is to give the computer the intelligence of human vision, so that the computer can quickly and accurately recognize the object on the input images. However, in the recognition process such factors as light, rotation and shield increase the difficulty of identifying the human head portrait images. In order to get better recognition performance, this paper studies the feature extraction of human head portrait based on SIFT (Scale Invariant Feature Transform). From the practical application, it can be seen that the approach proposed in this paper is feasible and is of good recognition performance.

Despite the appearance of high-tech human computer interface (HCI) devices, pattern recognition and gesture recognition with single camera are still playing vital role in research. A real-time human-body based algorithm for hand gesture recognition is proposed in this paper. The basis of our approach is a combination of moving object segmentation process and skin color detector based on human body structure to obtain the moving hands from input images, which is able to deal with the problem of complex background and random noises, and a rotate correction process for better finger detection. With ten fingers detected, more than 1000 gestures can be recognized before concerning motion paths. This paper includes experimental results of five gestures, which can be extended to other conditions. Experiments show that the algorithm can achieve a 99 percent recognition average rate and is suitable for real-time applications.

In this paper we propose a new steganographic method, which based on wet paper codes and wavelet transformation. The method is designed to embed secret messages in images' wavelet coefficients and depends on images' texture characters in local neighborhood. The receivers can extract secret bits from carrier images only by some matrix multiplications without knowing the formulas written by senders, which further improves steganographic security and minimizes the impact of embedding changes. The experimental results show that our proposed method has good robust and visual concealment performance and proves out it's a practical steganographic algorithm.

Purpose of this paper raise a vehicle lane departure warning system based on the machine vision. It does not need to use the parameters of the camera which do the road marking recognition system installed in the interior of the camera by algorithms. Regarding the time line of the intelligent transport system, it is to solve the various problems possibly arising from driving on the road. This system is mainly for the warning of the unexpected departure of vehicle. The method is to use the digital camera to capture continuous images and identify the vehicle moving direction by the detection of the left and right markings, as well as forecast the driving direction of the vehicle for the reference of vehicle departure warning. In this paper, the used algorithms include brightness adjustment, binarization, dilation, erosion, and edge detection image processing techniques.

The research on the color uniformity of the tiled multiple projectors display systems gets more and more attention. In this paper, taking the tiled two-projector display system as a case, the color calibration method based on ICC color management mechanism was proposed and used to achieve the color uniformity the non-overlapping projected region firstly. And the sectoring parabola interpretation algorithm was used to achieve the color uniformity of the overlapping projected region. The research content of this paper includes: ①The ICC profile of the projector based on matrix model was calculated and generated; ②The ICC profile of the projector based on 3-dimensions lookup table model was calculated and generated; ③The color-matching precision of the above two types of ICC profiles were compared by the color space conversion experiment, and the feasibility of color calibration method of the non-overlapping projected region based on ICC mechanism was verified; ④Finally, the feasibility of color calibration method of the overlapping projected region based on sectoring parabola interpretation algorithm was verified by Quest3D development platform.

Image mosaic (Mosaic) for a given image sequence is the first image sequence alignment positioning, and then fusion spliced to produce a seamless, high-resolution large-scale scene images. This paper discusses the calculation model in the wavelet transform in image processing and wavelet transform image stitching. This paper presents the optimal image mosaic method based on Wavelet transform and introduces a seamless optimization algorithm based on wavelet transform and its validity through a concrete example simulation.

In this paper, we propose an approach to automatic great-scene 3D reconstruction based on UAV sequence images. In this method, Harris feature point and SIFT feature vector is used to distill image feature, achieving images match; quasi-perspective projection model and factorization is employed to calibrate the uncalibrated image sequences automatically; Efficient suboptimal solutions to the optimal triangulation is plied to obtain the coordinate of 3D points; quasi-dense diffusing algorithm is bestowed to make 3D point denseness; the algorithm of bundle adjustment is taken to improve the precision of 3D points; the approach of Possion surface reconstruction is used to make 3D points gridded. This paper introduces the theory and technology of computer vision into great-scene 3D reconstruction, provides a new way for the construction of 3D scene, and provides a new thinking for the appliance of UAV sequence images.

Airborne LiDAR is a new kind of surveying technology of remote sensing which developed rapidly during recent years. Raw laser scanning point clouds data include terrain points, building points, vegetation points, outlier points, etc.. In order to generate digital elevation model (DEM) and three-dimensional city model,these point clouds data must be filtered. Mathematical morphology based filtering algorithm, slope based filtering algorithm, TIN based filtering algorithm, moving surface based filtering algorithm, scanning lines based filtering algorithm and so on several representative filtering algorithms for LiDAR point clouds data have been introduced and discussed and contrasted in this paper. Based on these algorithms summarize the studying progresss about the filtering algorithm of airborne LiDAR point clouds data in home and abroad. In the end, the paper gives an expectation which will provides a reference for the following relative study.

In the publishing and printing applications, hidden data is embedded into images for copyright protection and ownership generally. In this paper, a reasonable data hiding method based on noise-balanced error diffusion (NBEDF) is proposed, which is applied in color halftone image. Color image is firstly separated into grayscale images from RGB color space to CMYK color space. Secondly, Floyd-Steinberg error diffusion operator is used, and halftone images will be obtained. Finally,through NBEDF, hidden data is embedded in the halftone image which contains the largest amount of information. The experimental results show that hidden information can be visible , when the corresponding decoded image overlays the color image with hidden information. The data hiding method proposed in this paper can be well applied on security printing.

Measuring area of irregular shapes is essential for many applications in Geomatics engineering, Civil engineering, Agricultural sciences, and Medical sciences. In this era of digital images, a problem frequently encountered, when it is required to determine the area of irregular shapes such as irregular properties, contour lines, a parcel of land, drainage basins, lakes, ponds, wounds and tumors in human organs, swimming pools, and so on. This paper addresses this problem, and aims at developing a semi-automatic method that can be used as a software tool for area measurement of irregular shapes in digital images. The developed method is relatively straightforward and based on the raster image in which each spatial location has a pixel associated with it, and by definition each pixel will occupy a certain amount of area. The algorithm used in this method is based on spatial data in form of pixel coordinates. The algorithm is implemented in a computerized model developed in Microsoft Windows Visual C++6, and was equipped with Graphical User Interface (GUI) to friendly enable users to enter the required parameters. The experiment results using various sources of raster data, including satellite images, scanned map, medical images, and CAD drawings show that the developed software tool named (Area_IrreShape) is found to be effective, portable, easy to use, and accurate. However the cell size or the spatial resolution of the raster image is a key factor for the accuracy of measuring area by the developed software tool, and as such the accuracy increases as the size of the cell decreases. Finally, it can be concluded that the semi-automatic method developed in this paper is ideal for many applications for irregular or regular shapes, particularly where precise area measurement of large irregular two dimensional shapes in digital images is needed.

In reverse engineering and rapid prototyping, several intermediate contours interpolated between adjacent two-layer ICT slice are needed to meet the requirement of rapid prototyping. A method of linear interpolation based on minimum distance is adopted in this paper. On the basis of the research on interpolation problem between single contours, some researches on the interpolation problem of multiply contours was done in this paper. Satisfactory results are attained by the experiments of a vehicle engine.