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In this paper, a real-time implementation of pitch shifting with use of phase vocoder algorithm is presented. The goal was to create a system that would allow to process audio signal in real time with use of a general purpose microcontroller. The task was a challenge due to relative complexity of the algorithm and limited computational capacity of the microcontroller, whose architecture is by nature much more universal than that of dedicated digital signal processors. The results of experiments with the developed system are presented and discussed in the paper.

An analysis of the part deformation in the face turning of the grooves was presented. A face-grooving process was performed on the disc-shaped part made of titanium alloy Ti6Al4V. Investigations were performed in two stages. First, experimental studies were conducted to determine the level of the cutting forces for variable wall thickness and cutting data. In the second step of investigations, a computer simulation of the disc flange deformation was performed using finite element method in the NX Siemens software. Based on the analysis of the research results, the dependence of the direction and value of the cutting force on the deformation value has been determined.

Process of eye tomogram obtaining by means of optical coherent tomography is studied. Stages of idiopathic macula holes formation in the process of eye grounds diagnostics are considered. Main stages of retina pathology progression are determined: Fuzzy logic units for obtaining reliable conclusions regarding the result of diagnosis are developed. By the results of theoretical and practical research system and technique of retinal macular region of the eye state analysis is developed ; application of the system, based on fuzzy logic device, improves the efficiency of eye retina complex.

Detection of genomics rearrangements is a tough task, because of the size of data to be processed. As genome sequences may consist of hundreds of millions symbols, it is not only practically impossible to compare them by hand, but it is also complex problem for computer software. The way to significantly accelerate the process is to use rearrangement detection algorithm based on unique short sequences called markers. The algorithm described in this paper develops markers using base genome and find the markers positions on other genome. The algorithm has been extended by support for ambiguity symbols. Web application with graphical user interface has been created using three-layer architecture, where users could run the task simultaneously. The accuracy and efficiency of proposed solution has been studied using generated and real data.

The optical-electronic system for measuring of geometrical parameters of micrometrical objects is a difficult process that requires the observance of certain features designing or improvement. The observance of that will provide a higher measurement accuracy compared with the accuracy metrics of measurement that were developed without compliance with these design features. Every feature of the design reduces the error of the functioning of individual nodes of the system or errors in nodes under the influence of various internal or external factors. When reducing or eliminating each factor of occurrence of the error, respectively, will increase the overall measurement accuracy. In this work, the result of introducing measurement error for each factor is determined experimentally and proved the correctness of such actions. Experimental researches of the measurement error to the stage of compliance with subtleties in the improvement of the opto-electronic system was 10 ± 1.5 μm, and after improvement with considering of the specifics of the design measurement error of geometrical parameters was 10 ± 0,33 μm.

Possibility of executing the carriers and borrowings by means of elementary additive transformations in the process of calculation in Fibonacci numerical system is substantiated. Methods of counting in the given numerical system, based on the usage of information redundancy are suggested. The methods consist in the fact that at every step executed all possible elementary addition transformations of code in the counter simultaneously with adding one. The suggested methods enable to construct up-, down- and up/down counters with high speed, independent on the data capacity and small hardware cost that linearly grow with the increase of the capacity. Schemes of structural organization of one digit for each of the suggested methods are given.

This paper presents basic methods of reversible circuit description. To design reversible circuit a set of gates has to be chosen. Most popular libraries are composed of three types of gates so called CNT gates (Control, NOT and Toffoli). The gate indexing method presented in this paper is based on the CNT gates set. It introduces a uniform indexing of the gates used during synthesis process of reversible circuits. The paper is organized as follows. Section 1 recalls basic concepts of reversible logic. In Section 2 and 3 a graphical representation of the reversible gates and circuits is described. Section 4 describes proposed uniform NCT gates indexing. The presented gate indexing method provides gate numbering scheme independent of lines number of the designed circuit. The solution for a circuit consisting of smaller number of lines is a subset of solution for a larger circuit.

This paper concerns the issues of construction and experimental tests of a temperature stabilization system for small resistance increments measurement circuits. After switching the system on, a PCB board heats up and the long-term temperature drift altered the measurement result. The aim of this work is reducing the time of achieving constant nominal temperature by the measurement system, which would enable decreasing the time of measurements in the steady state. Moreover, the influence of temperatures higher than the nominal on the measurement results and the obtained heating curve were tested. During the working process, the circuit heats up to about 32 °C spontaneously, and it has the time to reach steady state of about 1200 s. Implementing a USART terminal on the PC and an NI USB-6341 data acquisition card makes recording the data (concerning temperature and resistance) in the digital form and its further processing easier. It also enables changing the quantity of the regulator settings. This paper presents sample results of measurements for several temperature values and the characteristics of the temperature and resistance changes in time as well as their comparison with the output values. The object identification is accomplished due to the Ziegler-Nichols method. The algorithm of determining the step characteristics parameters and examples of computations of the regulator settings are included together with example characteristics of the object regulation.

In response to the slow running speed of the Deformable Part Model algorithm in the process of the pedestrian detection, this paper incorporated Cascade Detection algorithm and Branch-and-Bound algorithm into a fast pedestrian detection algorithm which is based on Deformable Part Model. In a pedestrian detection process, a sequence model evaluates individual parts sequentially to quickly prune most of the smaller possible objects. This aims to accelerate the process of object positioning, and to optimize global classification results in all possible image regions. Meanwhile, the boundaries of the maximum are adopted to search the clipping operation of the window. In order to improve detection speed without compromising the accuracy of the detection, this paper increase the number of the part models involved. According to the experimental results on INRIA data set, the proposed algorithm successfully improved the accuracy and the speed of detection.

In this paper, we propose a method for target detection and tracking in infrared video. The target is defined by its location and extent in a single frame. In the initialization process, we use an adaptive threshold to segment the target and then extract the fern feature and normalize it as a template. The detector uses the random forest and fern to detect the target in the infrared video. The random forest and fern is a random combination of 2bit Binary Pattern, which is robust to infrared targets with blurred and unknown contours. The tracker uses the gray-value weighted mean-Shift algorithm to track the infrared target which is always brighter than the background. And the tracker can track the deformed target efficiently and quickly. When the target disappears, the detector will redetect the target in the coming infrared image. Finally, we verify the algorithm on the real-time infrared target detection and tracking platform. The result shows that our algorithm performs better than TLD in terms of recall and runtime in infrared video.

Multi-object tracking is particularly challenging in many scenarios with similar appearance and frequent occlusions among targets. In this paper, we present an online detection-based multi-object tracking method. In each frame, kernerlized convolution filter are adopted to track isolated and un-occluded targets. To overcoming fixed scale in KCF, trackers are associated with detection responses. If a target is associated with a detection, then the target size is updated by the average of this detection size and the previous estimated size. When occlusions are detected, the multiple interaction among targets is formulated as an optimization problem and we explore two-layer hierarchical Particle Swarm Optimization algorithm for the optimal solution. The first layer is designed for the superficial targets which is visible. The second layer is designed for the bottom occluded targets which can guided by first visible layer and we propose to incorporate the attractive force into the particle evolution process. Experimental results on public datasets demonstrate that our proposed method alleviating drifting problem and effectively reduces ID switches and lost trajectories.

Endoscopy imaging is utilized to provide a realistic view about the surfaces of organs inside the human body. Owing to the damp internal environment, these surfaces usually have a glossy appearance showing specular reflections. For many computer vision algorithms, the highlights created by specular reflections may become a significant source of error. In this paper, we present a novel method for restoration of the specular reflection regions from a single image. Specular restoration process starts with generating a substitute specular-free image with RPCA method. Then the specular removed image was obtained by taking the binary weighting template of highlight regions as the weighting for merging the original specular image and the substitute image. The modified template was furthermore discussed for the concealment of artificial effects in the edge of specular regions. Experimental results on the removal of the endoscopic image with specular reflections demonstrate the efficiency of the proposed method comparing to the existing methods.

The digital camouflage technology arranges different color mosaics according to a certain rules, compared with traditional camouflage, it has more outstanding results deal with different distance reconnaissance. The better result of digital camouflage is mainly attributed to spatial color mixture, and is also a key factor to improve digital camouflage design. However, the research of space color mixture is relatively lack, cannot provide inadequate support for digital camouflage design. Therefore, according to the process of spatial color mixture, this paper proposes an effective parameter, spatial-color-mixture ratio, to characterize the degree of spatial color mixture. The experimental results show that spatial-color-mixture ratio is feasible and effective in practice, which could provide a new direction for further research on digital camouflage.

We present a spatial domain image watermarking for printed and scanned documents. In the watermark embedding process, a watermark image is embedded into the blue color component of a white color image. The result is overlaid with information, and printed out on a piece of paper. In the watermark extraction process, a printed document is first scanned back to obtain an electronic copy. Geometric distortions from the printing and scanning processes are then reduced by an image registration technique based on affine transformation. All watermarked components are used to determine a threshold for watermark bits extraction. The performance of the proposed watermarking method was investigated based on different scanning resolutions, printing quality modes, and printable materials. Watermark extraction from ripped, crumpled, and wet documents was also investigated. The promising results demonstrate the effectiveness of the proposed method.

Landscape structures and process on different scale show different characteristics. In the study of specific target landmarks, the most appropriate scale for images can be attained by scale conversion, which improves the accuracy and efficiency of feature identification and classification. In this paper, the authors carried out experiments on multi-scale classification by taking the Shangri-la area in the north-western Yunnan province as the research area and the images from SPOT5 HRG and GF-1 Satellite as date sources. Firstly, the authors upscaled the two images by cubic convolution, and calculated the optimal scale for different objects on the earth shown in images by variation functions. Then the authors conducted multi-scale superposition classification on it by Maximum Likelyhood, and evaluated the classification accuracy. The results indicates that: (1) for most of the object on the earth, the optimal scale appears in the bigger scale instead of the original one. To be specific, water has the biggest optimal scale, i.e. around 25-30m; farmland, grassland, brushwood, roads, settlement places and woodland follows with 20-24m. The optimal scale for shades and flood land is basically as the same as the original one, i.e. 8m and 10m respectively. (2) Regarding the classification of the multi-scale superposed images, the overall accuracy of the ones from SPOT5 HRG and GF-1 Satellite is 12.84% and 14.76% higher than that of the original multi-spectral images, respectively, and Kappa coefficient is 0.1306 and 0.1419 higher, respectively. Hence, the multi-scale superposition classification which was applied in the research area can enhance the classification accuracy of remote sensing images .

The Mask Data Correctness Check (MDCC) is a reticle-level, multi-layer DRC-like check evolved from mask rule check (MRC). The MDCC uses extended job deck (EJB) to achieve mask composition and to perform a detailed check for positioning and integrity of each component of the reticle. Different design patterns on the mask will be mapped to different layers. Therefore, users may be able to review the whole reticle and check the interactions between different designs before the final mask pattern file is available. However, many types of MDCC check results, such as errors from overlapping patterns usually have very large and complex-shaped highlighted areas covering the boundary of the design. Users have to load the result OASIS file and overlap it to the original database that was assembled in MDCC process on a layout viewer, then search for the details of the check results. We introduce a quick result-reviewing method based on an html format report generated by Calibre® RVE. In the report generation process, we analyze and extract the essential part of result OASIS file to a result database (RDB) file by standard verification rule format (SVRF) commands. Calibre® RVE automatically loads the assembled reticle pattern and generates screen shots of these check results. All the processes are automatically triggered just after the MDCC process finishes. Users just have to open the html report to get the information they need: for example, check summary, captured images of results and their coordinates.

It has been still highly required for cost efficient solution with easy operation for full-automated CD measurement for line width about 500nm up to 5μm on photomask, because it is frequently use such photomask in the process of manufacturing MEMS sensor for IoT and some devices made in BCD (Bipola CMOS DMOS). As reply to such demand in photomask manufacturing field, we try to take a low noise digital camera technology and LED light source for i-line, which are recently developed, into new measuring tool in order to achieve 1nm (3σ) repeatability for line width measurement between 300nm to 10μm. In addition, for the purpose of full-automated operation, it is very important to find where an initial target line in dense pattern. To achieve such auto line detection precisely, we have improved accuracy of high precision stage (20nm as 3σ) and an alignment algorithm of MEMS Stepper to combine with this tool. As for user-friendly interface, Windows based software helps a lot for not only the operation but also recipe creation or edition in Excel. Actually, in the MEMS manufacturing process, there are various photomasks which need to be check and measure frequently therefore various recipe files are also have to be created and edited frequently.. In order to meet such a requirement in photomask management, we try to make it true by mixing old and new techniques together into one system, which comes to fully automated and cost efficient tool with 1nm repeatability in CD measurement.

Over the last two decades, eBeam mask writers have added inline correction features. Particularly when minimum feature sizes on mask went below 100nm a decade ago, the need for more precision within a reasonable write time increased the demand for more corrections. Inline correction is better for turnaround time and throughput, but inline correction is computationally limited because it is unacceptable for computation to limit the machine write time. Simultaneously, the same need for linearity correction, printability enhancement, and resilience to manufacturing variation has caused much innovation in offline mask data preparation and mask process correction. Typically, the writer performs inline correction for backscatter, fogging, loading, charging and thermal effects, but leaves With multi-beam writers, the write time is independent of shape count. Any set of input shapes is rasterized to a set of arrays of equal sized pixels that are each independently dosed to write the desired shapes. Multi-beam writers also have a certain minimum write time that is required for writing even a very small number of simple shapes. This gives rise to the possibility of providing linearity correction features, even for the short-range effects as inline correction in the writer. Such inline correction has zero impact on throughput and turnaround time of mask making. This paper introduces the GPU-accelerated inline linearity correction capability of the NuFlare MBM-1000 for the first time.

Inverse Lithography Technology (ILT) is becoming the choice for Optical Proximity Correction (OPC) of advanced technology nodes in IC design and production. Multi-beam mask writers promise significant mask writing time reduction for complex ILT style masks. Before multi-beam mask writers become the main stream working tools in mask production, VSB writers will continue to be the tool of choice to write both curvilinear ILT and Manhattanized ILT masks. To enable VSB mask writers for complex ILT style masks, model-based mask process correction (MB-MPC) is required to do the following: 1). Make reasonable corrections for complex edges for those features that exhibit relatively large deviations from both curvilinear ILT and Manhattanized ILT designs. 2). Control and manage both Edge Placement Errors (EPE) and shot count. 3. Assist in easing the migration to future multi-beam mask writer and serve as an effective backup solution during the transition. In this paper, a solution meeting all those requirements, MB-MPC with GPU acceleration, will be presented. One model calibration per process allows accurate correction regardless of the target mask writer.

For many optical systems, mainly in photography, the digital correction of distortion and lateral color aberration is a common step in the image processing pipeline. It is based on images of calibration targets and the determination of coefficients for a correction model. These coefficients are specific for the optical system which forms the aerial image for the sensor. If an exchange of the optical system is necessary, e.g. for offering optics for several applications like macro mode, wide-angle or tele-photo, the entire optical system is typically exchanged and not only parts of it. Using a technique for digital identification of the optical system, e.g. via an electronic interface, the corresponding correction coefficients can be obtained and applied. If the optical system to be exchanged is only a part of the entire optical system, the situation is more difficult. As an example, this is the case in the field of digital microscopy, where objective lenses with different numerical apertures and magnifications are available for the same microscopic body. These objective lenses are no image forming optical systems and need at least a tube lens to produce an image for capturing with a sensor. Both optical systems produce contributions to the resulting overall aberrations, e.g. distortion and lateral color aberration. For a particular pairing, coefficients for a correction model can be calibrated and applied. But in the case of an exchange of the objective, only a part of the optical system changes and a new calibration is needed. We will show how this problem can be solved using a mathematical operation and individual calibration of the distinct parts of the optical system. The advantage is, that the parts of the optical system can be arbitrarily combined and the correction-model coefficients of the combination can be computed from the corresponding coefficients of the individual parts. Hence, there’s no need to calibrate every possible combination or to manage a calibration process at the customer’s location. In addition, the manufacturing and calibration of objectives and tube lenses may take place at different locations. Furthermore, the optical design can benefit from the digital aberration correction although it is made up of interchangeable components.

Stent quality control is a highly critical process. Cardiovascular stents have to be inspected 100% so as no defective stent is implanted in a human body. However, this visual control is currently performed manually and every stent could need tenths of minutes to be inspected. In this paper, a novel optical inspection system is presented. By the combination of a high numerical aperture (NA) optical system, a rotational stage and a line-scan camera, unrolled sections of the outer and inner surfaces of the stent are obtained and image-processed at high speed. Defects appearing in those surfaces and also in the edges are extremely contrasted due to the shadowing effect of the high NA illumination and acquisition approach. Therefore by means of morphological operations and a sensitivity parameter, defects are detected. Based on a trained defect library, a binary classifier sorts each kind of defect through a set of scoring vectors, providing the quality operator with all the required information to finally take a decision. We expect this new approach to make defect detection completely objective and to dramatically reduce the time and cost of stent quality control stage.

Calibration which defines the relationship between the phase and depth data is the important part of the fringe projection profilometry. In practice, the inherently nonlinear and spatially variable relationship between the absolute phase of the projected fringe and the object surface depth without using telecentric lens make calibration problematic in the measurement of small object. In order to obtain this problem, a flexible, simple telecentric three dimensional measurement system is proposed. Because of the characteristic that the size of object will not change with depth in telecentric imaging, the absolute phase is linear with the depth and the process of calibration become simpler. The experiment result indicate that the standard deviation of calibration result at z coordinate is within 5 μm, while that at x and y coordinate is within 3 μm. Three-dimensional shape reconstruction of a coin value ¥1 and measurement of central circle points of the calibration target further verify the validity of the proposed calibration method.

Zeltmann, et al. demonstrated that structural integrity and other quality damage to objects can be caused by changing its position on a 3D printer’s build plate. On some printers, for example, object surfaces and support members may be stronger when oriented parallel to the X or Y axis. The challenge presented by the need to assure 3D printed object orientation is that this can be altered in numerous places throughout the system. This paper considers attack scenarios and discusses where attacks that change printing orientation can occur in the process. An imaging-based solution to combat this problem is presented.

Polishing as a step of the manufacturing process is not only used in the finishing of optical elements made out of glass. An increasing number of applications needs shiny or glossy surfaces. For these parts, the specified roughness has to be achieved by a final polishing step while keeping or improving the final shape. The goal of the presented research is to predict the material removal that occurs during the polishing process by a simulation based on finite element modelling (FEM). The presented finite element simulation model for PMMA is based on the material parameters for workpiece and polishing tool. Compared to previous research on aspherical elements made out of glass [1], the model allows the description of the process based on material parameters get out the data sheets. The data derived from the finite element modelling is compared with the polishing results on plastic materials (PMMA). Results of the polishing tests compared with the simulated values will be reported.

The trend in the optic industry shows, that it is increasingly important to be able to manufacture complex lens geometries on a high level of precision. From a certain limit on the required shape accuracy of optical workpieces, the processing is changed from the two-dimensional to point-shaped processing. It is very important that the process is as stable as possible during the in point-shaped processing. To ensure stability, usually only one process parameter is varied during processing. It is common that this parameter is the feed rate, which corresponds to the dwell time. In the research project ArenA-FOi (Application-oriented analysis of resource-saving and energy-efficient design of industrial facilities for the optical industry), a touching procedure is used in the point-attack, and in this case a close look is made as to whether a change of several process parameters is meaningful during a processing. The ADAPT tool in size R20 from Satisloh AG is used, which is also available for purchase. The behavior of the tool is tested under constant conditions in the MCP 250 CNC by OptoTech GmbH. A series of experiments should enable the TIF (tool influence function) to be determined using three variable parameters. Furthermore, the maximum error frequency that can be processed is calculated as an example for one parameter set and serves as an outlook for further investigations. The test results serve as the basic for the later removal simulation, which must be able to deal with a variable TIF. This topic has already been successfully implemented in another research project of the Institute for Precision Manufacturing and High-Frequency Technology (IPH) and thus this algorithm can be used. The next step is the useful implementation of the collected knowledge. The TIF must be selected on the basis of the measured data. It is important to know the error frequencies to select the optimal TIF. Thus, it is possible to compare the simulated results with real measurement data and to carry out a revision. From this point onwards, it is possible to evaluate the potential of this approach, and in the ideal case it will be further researched and later found in the production.

While setting up grinding processes for optics fabrication, the optimum tool and process parameters have to be chosen. Unfortunately, datasheets of commercial grinding tools contain only information about grit type and size, bond material, tool shape etc., leaving out any information about process parameters to be applied or tool lifetime or performance. For this reason, tools and machining parameters are commonly adjusted during iterative experimental test runs using actual workpieces from production batches which is time consuming, expensive and without guarantee that the optimum set of machining parameters are achieved. In this paper we present a method to determine grinding tools process window for a given workpiece material. That way, ideal machining parameters can be determined offline for maximum reliability and productivity. In addition, the gained data provides the basis to identify the most suitable grinding tool for the desired application.

The industrial production of components for applications in the area of precision optics has a long-standing tradition in Germany. As in almost all branches of industry, the external circumstances, processes and products have changed over time. Large lots are becoming less frequent and the demand for special components is growing. In order to meet these requirements, it is necessary to adapt the production processes quickly and flexibly. In the field of chemo-mechanical polishing (CMP), this means that in addition to the process parameters such as speed, pressure and feed, the task-specific adaptation of suspension and polishing pad carriers gain in importance. Along with these changes, it is becoming increasingly important to compare and evaluate the properties of the various polishing suspensions. The procedures according to DIN 58750-3 and DIN 58750-4 are suitable for this purpose. Due to the clearly defined procedures and the constant boundary conditions, different suspensions can be compared and evaluated. The study presented here shows that this method can also lead to misinterpretations. Known relationships, such as the influence of the polishing pad, the concentration of the suspension and the influence of the processed materials play an important role. An extension of the procedure of DIN 58750-3 for the test of a polishing agent can help in a task-specific characterization of polishing slurries.

In these days industry 4.0 resounded throughout the land and means the fourth industrial revolution. The industry has to tackle the task of a flexible and customer-oriented production. Therefor the need of sensor systems for the measurement of temperature and load, the two most important categories in production, is rising. For getting the real specification during the production process the integration of sensor elements in high load regions of machinery is very important. Thus wear resistant thin film sensor systems directly applied onto the surface of plant components are in development. These multilayer systems combine excellent wear resistance with sensory behaviour. The sensor data will lead to a deeper process understanding, to optimization of simulation tools, to reduction of rejects and to an improvement of flexibility in production.

The process of conventional 3D printing begins by first build a 3D model, then convert to the model to G-code via a slicer software, feed the G-code to the printer, and finally start the printing. The most simple and popular 3D printing technique is Fused Deposition Modeling. However, in this method, the printing path that the printer head can take is restricted by the G-code. Therefore the printed 3D models with complex pattern have structural errors like holes or gaps between the printed material lines. In addition, the structural density and the material’s position of the printed model are difficult to control. We realized the G-code editing, Fabrix, for making a more precise and functional printed model with both single and multiple material. The models with different stiffness are fabricated by the controlling the printing density of the filament materials with our method. In addition, the multi-material 3D printing has a possibility to expand the physical properties by the material combination and its G-code editing. These results show the new printing method to provide more creative and functional 3D printing techniques.

Methods of artificial intelligence are a good solution for weather phenomena forecasting. They allow to process a large amount of diverse data. Recirculation Neural Networks is implemented in the paper for the system of thunderstorm events prediction. Large amounts of experimental data from lightning sensors and electric field mills networks are received and analyzed. The average recognition accuracy of sensor signals is calculated. It is shown that Recirculation Neural Networks is a promising solution in the forecasting of thunderstorms and weather phenomena, characterized by the high efficiency of the recognition elements of the sensor signals, allows to compress images and highlight their characteristic features for subsequent recognition.

Volume Holographic Optical Elements (vHOEs) gained wide attention as optical combiners for the use in smart glasses and augmented reality (SG and AR, respectively) consumer electronics and automotive head-up display applications. The unique characteristics of these diffractive grating structures – being lightweight, thin and flat – make them perfectly suitable for use in integrated optical components like spectacle lenses and car windshields. While being transparent in Off-Bragg condition, they provide full color capability and adjustable diffraction efficiency. The instant developing photopolymer Bayfol® HX film provides an ideal technology platform to optimize the performance of vHOEs in a wide range of applications. Important for any commercialization are simple and robust mass production schemes. In this paper, we present an efficient and easy to control one-beam recording scheme to copy a so-called master vHOE in a step-and-repeat process. In this contact-copy scheme, Bayfol® HX film is laminated to a master stack before being exposed by a scanning laser line. Subsequently, the film is delaminated in a controlled fashion and bleached. We explain working principles of the one-beam copy concept, discuss the opto-mechanical construction and outline the downstream process of the installed vHOE replication line. Moreover, we focus on aspects like performance optimization of the copy vHOE, the bleaching process and the suitable choice of protective cover film in the re-lamination step, preparing the integration of the vHOE into the final device.

We present a general strategy for characterizing the reaction and diffusion kinetics of polymeric holographic recording media by which key processes are decoupled and independently measured. The separate processes are combined into a predictive model that is shown to make accurate quantitative predictions of index response over three orders of exposure dose (~1 to ~10 3 mJ/cm 2 ) and feature size (0.35 to 500 microns) for a model material similar to commercial media. Several critical performance concepts also emerge from the model, including a prediction of a formulation’s maximum potential index response, insight into why a particular material may not achieve this maximum and the process that limits the recording resolution.

Crop yield estimation is an important task in product management and marketing. Accurate yield prediction helps farmers to make better decision on cultivation practices, plant disease prevention, and the size of harvest labor force. The current practice of yield estimation based on the manual counting of fruits is very time consuming and expensive process and it is not practical for big fields. Robotic systems including Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV), provide an efficient, cost-effective, flexible, and scalable solution for product management and yield prediction. Recently huge data has been gathered from agricultural field, however efficient analysis of those data is still a challenging task. Computer vision approaches currently face diffident challenges in automatic counting of fruits or flowers including occlusion caused by leaves, branches or other fruits, variance in natural illumination, and scale. In this paper a novel deep convolutional network algorithm was developed to facilitate the accurate yield prediction and automatic counting of fruits and vegetables on the images. Our method is robust to occlusion, shadow, uneven illumination and scale. Experimental results in comparison to the state-of-the art show the effectiveness of our algorithm.

The modern needs of the electro-optical market for small low-power and light-weight IR systems are impelling research and development of High Operating Temperature (HOT) IR detectors, requiring development of dedicated “HOT” cryocoolers. The development of cryocoolers with emphasis on the “SWAP 3 ” configuration means small size, low weight, improved performance, low power consumption and low price, in order to optimize IDDCA for future hand held thermal sights. This paper will present the development and the progress made with the new "HOT" cryocooler, including customer data after the evaluation process, performances achieved using a common cold finger, test results update on a large series of production coolers, life and qualification test update and acoustic noise reduction. All the above mentioned information relates to the FPA temperature range of 130 - 200K for various cryocooler models based on rotary and linear design concepts. The paper will also review the progress with the latest development activities implemented in the cryocoolers and the electronic control modules in order to improve reliability and minimize regulated power consumption.

Hyperspectral images have been used in many areas including city planning, mining and military decision support systems. Hyperspectral image analysis techniques have a great potential for vegetation detection and classification with their capability to identify the spectral differences across the electromagnetic spectrum due to their ability to provide information about the chemical compositions of materials. This study introduces a vegetation detection method employing Artificial Neural Network (ANN) over hyperspectral imaging. The algorithm employed backpropagation MLP algorithm for training neural networks. The performance of ANN is improved by the joint use with Spectral Angle Mapper(SAM). The algorithm first obtains the certainty measure from ANN, following the completion of this process, every pixels’ angular distance is computed by SAM. The certainty measure is divided by angular distance. Results from ANN, SAM and Support Vector Machine (SVM) algorithms are compared and evaluated with the result of the algorithm. Limited number of training samples are used for training. The results demonstrate that joint use of ANN and SAM significantly improves classification accuracy for smaller training samples.

In an application of side-attack explosive hazard (SAEH) detection, one challenge is detecting occluded targets. Forward-looking ground penetrating radar (FLGPR) is a sensor that has the capability to handle this type of problem since this frequency can penetrate occlusion and detect the explosive. However, the explosive can be concealed by multiple types of objects along the side of the road, such as rocks, vegetation, trash, etc. In FLGPR imaging space, these clusters of occlusion come in many shapes and sizes. The log Gabor descriptor, which has the advantage of separating different types of textures, is a potential solution for the aforementioned issue. However, in order to fully utilize the log Gabor filter bank, there are many parameters that need to be handcrafted for each specific problem. Since the possibility of designing a filter bank is endless, brute-force search is not possible. An additional element to be considered is the size of the filter bank, since a large filter bank requires more computation time. In this paper, we propose the use of multi-objective optimization based on an evolutionary algorithm to streamline the process of designing a log Gabor filter bank. The objectives of the optimization are to design a filter bank that can separate the explosive hazards from false alarm hits while keeping the size of the filter bank to a minimum. The data we use to validate our proposed method was collected on arid lanes by a MIMO FLGPR system on board of the U.S. Army prototype vehicle. The experiments are designed to measure the improvement of the optimization over the manual tuning and to demonstrate the impact of the optimization’s parameters on the performance of the filter bank.

Search planning for UUV missions involves a complex optimization problem over multiple degrees of freedom. The detection performance of individual searches is governed by the local environment and the sensor settings that determine the rate at which target objects of interest can be identified. This paper addresses some of the computational aspects of collaborative search planning when multiple search agents seek to find hidden objects (i.e. mines) in adverse local operating environments where the detection process is prone to false alarms. For these conditions, we apply a receiver operator characteristic (ROC) analysis to model detection performance and develop a Bayesian risk objective that enumerates the required number of detections for validation as part of the modeling paradigm. In this paper we consider an expanded optimization process whereby ROC operating points are optimized simultaneously for all validation criteria with the best performing combinations selected. Details of its application within a broader search planning context are discussed. An analysis of this optimization process is presented. Numerical results are provided to demonstrate the effectiveness of the approach.

In the past, chemical incidents or attacks have often involved mixtures of chemicals or fractional formulations of toxic compounds. Terrorist groups are also likely to generate new toxic chemical agents. These situations involve unknown compounds and thus may be undetectable using traditional methods. Indeed, standoff gas detection with infrared devices traditionally relies on the comparison between measured signal and a library of signals included in a database. Observing the gas absorption in infrared band III (LWIR 8-14 μm), our multispectral infrared camera is used to detect gas clouds up to a range of several kilometers, to provide identification of gas type and to follow the motion of the cloud in real time. The approach described in this paper develops an algorithm that enables the device to detect gas even if the measured signature is not in the database – a pattern-matching-free algorithm. This detection process has been evaluated in the laboratory and subjected to significant experimental feedback. The results are a capability to detect unknown gases and gas mixtures.

Multisensor image fusion (e.g. IR with visual) is the process of combining relevant information from two or more images into a single image. The aim is to find an objective quality measure, which can be used in automatic applications, that correlates best with subjective observer trials. Not all combinations of image, algorithm, and test observer can be worked out. In this paper R. Fisher’s Design of Experiments approach based on Latin Squares is used for thinning out the number of experiments for each observer in such observer trials while preserving exactness and reliability of the result.

Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

A vehicle classification system, which uses features based on radiometry, is developed for single band infrared (IR) image sequences. In this context, the process is divided into three components. These are moving vehicle detection, radiance estimation, and classification. The major contribution of this paper lies in the usage of the radiance values as features, other than the raw output of IR camera output, to improve the classification performance of the detected objects. The motivation behind this is that each vehicle class has a discriminating radiance value that originates from the source temperature of the object modified by the intrinsic characteristics of the radiating surface and the environment. As a consequence, significant performance gains are achieved due to the use of radiance values in classification for the utilized measurement system.

Image matching involves detecting the same points in two or multiple images that are captured from different viewpoints, at different time, and/or by different cameras. This paper presents using the image-matching-based techniques to carry out the static and dynamic 3D shape measurements. The process contains two crucial steps: (1) calibrate the cameras to get the intrinsic and extrinsic parameters; (2) perform matching of pixel points to detect the location disparities of the same physical points in the involved two or multiple images. A number of experiments are shown to demonstrate the applications to 3D shape, deformation, motion and vibration measurements.

Lensless imaging systems have the potential to provide new capabilities for lower size and weight configuration than traditional imaging systems. Lensless imagers frequently utilize computational imaging techniques, which moves the complexity of the system away from optical subcomponents and into a calibration process whereby the measurement matrix is estimated. We report on the design, simulation, and prototyping of a lensless imaging system that utilizes a 3D printed optically transparent random scattering element. Development of end-to-end system simulations, which includes simulations of the calibration process, as well as the data processing algorithm used to generate an image from the raw data are presented. These simulations utilize GPU-based raytracing software, and parallelized minimization algorithms to bring complete system simulation times down to the order of seconds. Hardware prototype results are presented, and practical lessons such as the effect of sensor noise on reconstructed image quality are discussed. System performance metrics are proposed and evaluated to discuss image quality in a manner that is relatable to traditional image quality metrics. Various hardware instantiations are discussed.

The effectiveness of various dynamic calibration targets emulating human respiration are analyzed. Potential advantages of these devices relate to easier calibration methods for human detection testing in through-wall and through-rubbles situations. The three devices examined possess spherical polyhedral geometries. Spherical characteristics were implemented due to the unique qualities spheres possess in regards to calibration purposes. The ability to use a device that is aspect independent is favorable during the calibration process. Rather than using a traditional, static calibration sphere, a dynamic, sphere-like device offers the ability to resemble breathing movements of the human body. This motion opens the door for numerous types of Doppler testing that is impossible in a static calibration device. Monostatic RCS simulations at 3 GHz are documented for each geometry. The results provide a visual way of representing the effectiveness of each design as a dynamic calibration target for human detection purposes.

Currently, when data is collected, it is usually collected for a specific need or situation. This includes text and image data. When a new need or situation arises, the data collection process repeats, often without referencing the original data collected for previous situations. Data Transpositioning is a search methodology that leverages the context of a previous manual search process, to formulate a new automated search with new results. As a result, the data collection process for one situation, can quickly be applied to another situation, but with less user effort. Thus, a set of new results can quickly be constructed without the user manually revisiting each of the originating sources. In the case of Content-Based Image Retrieval, the idea is to identify the content attributes of an image, such as a particular color, shape or texture, and apply changes to the originating query, and return a new set of results with the similar attributes. Data Transpositioning has been successfully applied to the result sets that contain text. Our goal is to continue this research beyond text to solve more complex problems in other domains, especially when image data are involved.

This paper presents an approach enabling localization and identification of foreign bodies in polymer materials applying a combined approach of x-ray imaging, imaging microscopy, optical coherence tomography and Raman imaging spectroscopy. The reliable detection of even small foreign bodies in polymer materials and parts designated for use in semiconductor manufacturing and processing machines is essential. Foreign bodies can in particular be metals, burnt particles of the polymer of the work piece, or intact or degenerated foreign polymers. In either case, all surfaces of e.g. a handling equipment that get in contact with the semiconductor material or process solutions have to be free of foreign bodies to ensure the integrity of the manufacturing process. Size, localization and material of the foreign body are main parameters that decide if a work piece has to be rejected. Current inspection systems may enable the localization of the foreign body, but are not capable of identifying the material and structure of the foreign body; many components with inclusions are therefore rejected as a precaution. This work aims towards the development of a combined sensor approach as part of an automatic quality assurance procedure which can be integrated in the fabrication process. X-ray imaging is used to identify metal foreign bodies. Imaging microscopy is used to detect foreign bodies on the surface of the polymer parts. Optical coherence tomography is used to measure the three-dimensional position and size of the foreign bodies. Raman imaging spectroscopy is used to identify the composition of the foreign bodies if they are located on the surface.

Optical fiber sensors are very useful to monitor the internal strain and temperature in composites during manufacturing and assembly as well as in practical operations. The authors have been using both multi-point and distributed strain monitoring techniques to characterize the internal state of composite structures. This paper reports some recent developments of life cycle monitoring and quality control of aerospace composite structures. Specifically, distributed sensing for large-scaled parts, through-thickness strain monitoring for complex-shaped parts, and direction-dependent cure shrinkage monitoring are described, highlighting wide applicability of embedded optical fiber sensors for intelligent process monitoring and quality assessment of composite parts.

In this paper, an impact monitoring system using fiber Bragg grating (FBG) sensors and vibro-haptic actuators have been introduced. The system is suggested for structural health monitoring (SHM) for unmmaned aerial vehicles (UAVs), by making a decision with human-robot interaction. The system is composed with two major subsystems; an on-board system equipped on UAV and an arm-wearable interface for ground pilot. The on-board system acquires impact-induced wavelength changes and performs localization process, which was developed based on arrival time calculation. The arm-wearable interface helps ground pilots to make decision about impact location themselves by stimulating their tactile-sense with motor vibration.

Additive Manufacturing provides the opportunity to fabricate components of nearly limitless complexity compared to that of traditional manufacturing techniques. However, thermal gyrations imparted into the material from the passing of the heat source cause challenges in fabricating complex structures with the proper process parameters. While the thermal history of the material can be simulated, validating the simulations requires access to thermal data generated through in-situ process monitoring. While generation of in-situ thermal data seems trivial, acquiring and developing reliable calibrations for metallic materials is difficult due to the physical state of the material transitioning from powder to liquid to a solid. To be discussed is the methodology taken to integrate IR in-situ process monitoring within the electron beam melting process and the approach developed to accurately correlate a materials emissivity to temperature during the build process. Further the wealth of information contained within the thermal data will be discussed in the context of understanding of microstructural evolutions within the material during the build process, identification of material defects, and ability to determining the similarity/repeatability of builds fabricated with identical processing parameters as based only on the thermal signature of the build.

The paper proposes a fully mechanical air curtain system that will be powered solely by harvested energy from common hinged doors. The average person uses this type of door several times a day with an almost unconscious amount of applied force and effort. This leads to a high potential of energy to be harvested in doorways that see high traffic and frequent operation7 . Frequently opened door entry ways have always been regarded as a major element that causes significant energy loss and contaminated air conditions in buildings6 . Private companies, particularly those with warehouses, have introduced commercial electrical air curtains to block the open entrances from invading cold air11. This project intends to introduce an original design of air curtain which operates fans only when the door opens and closes, by directly converting door motion to fan rotation without any electronic motor or power cable. The air stream created by this device will prevent the transfer of outside air and contaminants. Research will be conducted to determine the most efficient method of harvesting energy from door use, and the prototyping process will be conducted to meet the required performance of current air curtain models.