Synthetic aperture radar (SAR) is a widely used technique suited for real-time and all-weather imaging of natural surfaces and artificial objects. To improve image resolution and increase accuracy of radar cross secti...
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Synthetic aperture radar (SAR) is a widely used technique suited for real-time and all-weather imaging of natural surfaces and artificial objects. To improve image resolution and increase accuracy of radar cross section estimation the problem of statistical synthesis of signal processing algorithm in SAR is solved. Proposed method allows to form images with super-resolution in azimuth and range. Synthesis is performed using modern theory of radio engineering systems statistical optimization.
A student-built unmanned aerial system (UAS) was developed by the University of Hawaii Drone Technologies team for the 2017 Association for Unmanned Vehicle systems International (AUVSI) Student Unmanned Aerial System...
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A student-built unmanned aerial system (UAS) was developed by the University of Hawaii Drone Technologies team for the 2017 Association for Unmanned Vehicle systems International (AUVSI) Student Unmanned Aerial System (SUAS) competition, which simulates a search-and-rescue (SAR) mission. The UAS comprises a fixed-wing airframe integrated with flight control and communication components, and is capable of autonomous waypoint navigation, in-flight data transfer, aerial image capture with onboard imageprocessing, and aerial payload delivery. The UAS is capable of executing a 30-minute SAR mission in search of a simulated lost hiker. SAR tasks include autonomously navigating to a designated area, conducting a search for alphanumeric targets over a 370,000-m~2 search area, and autonomously dropping an 8-oz care package to the lost hiker. image-processing and computer-vision algorithms can correctly sense and identify the alphanumeric targets with 75% accuracy.
The article is devoted to solving the fundamental scientific problems of developing universal methods of video sequence processing for the detection and tracking of objects of *** work on the subject,authors designed ...
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The article is devoted to solving the fundamental scientific problems of developing universal methods of video sequence processing for the detection and tracking of objects of *** work on the subject,authors designed new methods and algorithms for universal monitoring systems for wide range of objects in the video sequences which could be implemented at miniaturized data processing *** this paper we describe a new method of search and recognition of point objects on a complex background,a new algorithm for the analysis of the found set of descriptors of local features to filter false positives filter local features,object detection criterion in the image,a new algorithm for the analysis of the trajectory of a point object on the basis of a recursive Kalman filter to predict the trajectory the movement of point objects.
Lack of Proper Information around Sri Lankan Historical Places cause to give false information. If ruins scattered around same place tourists are struggling to identify them. Sometimes there are small sign boards but ...
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Lack of Proper Information around Sri Lankan Historical Places cause to give false information. If ruins scattered around same place tourists are struggling to identify them. Sometimes there are small sign boards but they don't provide enough information. In this paper we address this challenge by using user captured image or search imaged. Our approach is produced a single document about identified places. System identify the places through training dataset using SVM. System will increase the accuracy of prediction by taking GPS data and user inputs necessarily. The evaluation shows that our approach is more accurate than the existing systems.
Digital tomosynthesis has an advantage of low radiation dose compared to conventional computed tomography (CT) by utilizing small number of projections (similar to 80) acquired over a limited angular range. It can pro...
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ISBN:
(数字)9781510607101
ISBN:
(纸本)9781510607095;9781510607101
Digital tomosynthesis has an advantage of low radiation dose compared to conventional computed tomography (CT) by utilizing small number of projections (similar to 80) acquired over a limited angular range. It can produce 3D volumetric data although they may have some artifacts due to incomplete sampling. Based upon these attractive merits, we developed a prototype digital tomosynthesis R/F system especially for the purpose of applications in chest imaging. Prototype chest digital tomosynthesis (CDT) R/F system contains an X-ray tube with high power R/F pulse generator, flat-panel detector, R/F table, electromechanical radiographic subsystems including precise motor controller, and a reconstruction server. For image reconstruction, users could select the reconstruction option between analytic and iterative methods. Reconstructed images of Catphan700 and LUNGMAN phantoms clearly and rapidly described the internal structures of the phantoms using graphics processing unit (GPU) programming. Contrast-to-noise ratio (CNR) values of the CTP682 module was higher in images using the simultaneous algebraic reconstruction technique (SART) than those using filtered back-projection (FBP) for all materials by factors of 2.60, 3.78, 5.50, 2.30, 3.70, and 2.52 for air, lung foam, low density polyethylene (LDPE), Delrin (R) (acetal homopolymer resin), bone 50% (hydroxyapatite), and Teflon, respectively. Total elapsed times for producing 3D volume were 2.92 sec and 86.29 sec on average for FBP and SART (20 iterations), respectively. The times required for reconstruction were clinically feasible. Moreover, the total radiation dose from the system (5.68 mGy) could demonstrate a significant lowered radiation dose compared to conventional chest CT scan. Consequently, our prototype tomosynthesis R/F system represents an important advance in digital tomosynthesis applications.
Compressed sensing became a vital tool for image or signal reconstruction with less number of samples compared with the Nyquist rate. Among the existing algorithms for reconstruction of an image using compressed sensi...
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ISBN:
(纸本)9781509044429
Compressed sensing became a vital tool for image or signal reconstruction with less number of samples compared with the Nyquist rate. Among the existing algorithms for reconstruction of an image using compressed sensing, orthogonal matching pursuit algorithm is cost effective in terms of computational complexity. This algorithm provides a solution for overdetermined and underdetermined systems by minimizing the error functions using least square. This work concentrates on the construction of dictionary which can be used to solve the sparsity based image denoising problem. In this paper, we constructed the dictionary using least square solution subjected to thresholding conditions such as hard, soft and semi-soft. Orthogonal matching pursuit (OMP) algorithm avoids the selection of the same atom in every iteration, due to the existence of orthogonal property between the residue and the atom selected from the dictionary. Thus, OMP algorithm results in precise image reconstruction. The proposed method is validated on four standard test images, such as Lena, Boat, Barbara and Cameraman with different noises such as salt & pepper noise, Gaussian noise and speckle noise with varying the percentage of noise level from 5% to 40%. Obtained results are evaluated by the quality metric peak-to-signal-noise ratio (PSNR) and compared with the existing wavelet based sparse image denoising. The experimental evaluation shows that the proposed method is better applicable to remove the speckle noise and salt & pepper noise when compared with the existing wavelet based sparse image denoising.
The usage of video surveillance systems increases more and more every year and protecting people privacy becomes a serious concern. In this paper, we present ASePPI, an Adaptive Scrambling enabling Privacy Protection ...
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The usage of video surveillance systems increases more and more every year and protecting people privacy becomes a serious concern. In this paper, we present ASePPI, an Adaptive Scrambling enabling Privacy Protection and Intelligibility. It operates in the DCT domain within the H.264 standard. For each residual block of the luminance channel inside the region of interest, we encrypt the coefficients. Whereas encrypted coefficients appear as noise in the protected image, the DC value is dedicated to restore some of the original information. Thus, the proposed approach automatically adapts the level of protection according to the resolution of the region of interest. Comparing to existing methods, our framework provides better privacy protection with some flexibilities on the appearance of the protected version yielding better visibility of the scene for monitoring. Moreover, the impact on the source coding stream is negligible. Indeed, the results demonstrate a slight decrease in the quality of the reconstructed images and a small percentage of bits overhead.
This paper presents a study on the exploitation of visual information from two points of view radically different. Computer vision is a branch of artificial intelligence that focuses on the extraction of useful inform...
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ISBN:
(纸本)9781509016457
This paper presents a study on the exploitation of visual information from two points of view radically different. Computer vision is a branch of artificial intelligence that focuses on the extraction of useful information in an image. image matching is a fundamental aspect of many problems in computer vision. Several algorithms have been developed for this purpose. Based on this research, this paper present all the previous work reviewed.
Robots are starting to be applied in areas which involve sharing space with humans. In particular, social robots and people will coexist closely because the former are intended to interact with the latter. In this con...
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Robots are starting to be applied in areas which involve sharing space with humans. In particular, social robots and people will coexist closely because the former are intended to interact with the latter. In this context, it is crucial that robots are aware of the presence of people around them. Traditionally, people detection has been performed using a flow of two-dimensional images. However, in nature, animals' sight perceives their surroundings using color and depth information. In this work, we present new people detectors that make use of the data provided by depth sensors and red-green-blue images to deal with the characteristics of human-robot interaction scenarios. These people detectors are based on previous works using two-dimensional images and existing people detectors from different areas. The disparity of the input and output data used by these types of algorithms usually complicates their integration into robot control architectures. We propose a common interface that can be used by any people detector, resulting in numerous advantages. Several people detectors using depth information and the common interface have been implemented and evaluated. The results show a great diversity among the different algorithms. Each one has a particular domain of use, which is reflected in the results. A clever combination of several algorithms appears as a promising solution to achieve a flexible, reliable people detector.
Rail transportation systems, which are commonly used in today's world, should be inspected at certain intervals for possible accidents. During the rail inspection, the physical vibration on rail lines causes a blu...
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ISBN:
(纸本)9781467395557
Rail transportation systems, which are commonly used in today's world, should be inspected at certain intervals for possible accidents. During the rail inspection, the physical vibration on rail lines causes a blurring effect on the images. Doing deblurring automatically requires information of blurring rates and specifying the parameters accordingly for deblurring. With this purpose, a test equipment which can move on rail lines and a camera system for the detection of blurring and deblurring is integrated with Inertial Measurement Unit (EMU) is promoted in this study. Then, with Attitude and Heading Reference System (AHRS) algorithm, the effect of blurring at the moment of the vibration is examined, point spread function (PSF) value is chosen dynamically and deblurring is achieved. In order to increase the accuracy rates of detection algorithms, a pretreatment method is proposed for detecting the blur effect and removing it.
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