This paper presents a novel monocular detection and tracking algorithm of vehicles applied to electronic vehicle coupling at close distances. For the sake of safety and reliability the vehicle to track is marked with ...
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This paper presents a novel monocular detection and tracking algorithm of vehicles applied to electronic vehicle coupling at close distances. For the sake of safety and reliability the vehicle to track is marked with a pattern. Such an application demands for measuring reliably and with high precision the position and orientation of the vehicle to follow relative to the pursuing vehicle. Additional requirements are real time capability with respect to standard PC hardware and robustness against strong vibrations, high illumination dynamics and other effects that an automotive imageprocessing application faces typically.
Digital imageprocessing is an actual task in the digital communication systems, IP-telephony and video conferencing, in digital television, and video surveillance. Digital processing of large video images takes a lot...
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ISBN:
(纸本)9781728173863
Digital imageprocessing is an actual task in the digital communication systems, IP-telephony and video conferencing, in digital television, and video surveillance. Digital processing of large video images takes a lot of time, especially if it happens in a real-time system. And, processing speed plays an important role in recognition of objects in video images received from IP-cameras in real time. This requires the use of modern technologies, and fast algorithms that increase the acceleration of digital imageprocessing. Acceleration problems have not been fully resolved till present. Today's realities are such that the development of accelerated imageprocessing programs requires a good knowledge of parallel and distributed computing. Both of these areas are united by the fact that both parallel and distributed software consists of several processes that together solve one common problem. This article proposes an accelerated method for the tasks of recognizing objects in video images received from IP-cameras using parallel and distributed computing technologies
This article describes the development of a dual-monitor visual stimulus generator that is used in neuroscience experiments with invertebrates such as flies. The experiment consists in the visualization of two fixed i...
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ISBN:
(纸本)9781424441242
This article describes the development of a dual-monitor visual stimulus generator that is used in neuroscience experiments with invertebrates such as flies. The experiment consists in the visualization of two fixed images that are displaced horizontally according to the stimulus data. The system was developed using off-the-shelf FPGA kits and it is capable of displaying 640x480 pixels with 256 intensity levels at 200 frames per second (FPS) on each monitor. A Raster plot of the experiment with the superimposed stimuli was generated as the result of this work. A novel architecture was developed, using the same DOT Clock for both monitors, and its implementation generates a perfect synchronism in both devices.
WWW image retrieval systems can retrieve the corresponding images to the query keyword from WWW, however every system cannot retrieve suitable images with high precision. In this paper, a new WWW image retrieval syste...
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ISBN:
(纸本)0780393619
WWW image retrieval systems can retrieve the corresponding images to the query keyword from WWW, however every system cannot retrieve suitable images with high precision. In this paper, a new WWW image retrieval system using the image knowledge database is proposed. This system can show more suitable images by filtering retrieval results of the conventional system. If the query keyword is not registered in the database, the user must select the suitable ones from image data retrieved by the conventional system, and then features of selected images are registered into the database as the supervised data. If the query keyword is the registered one, more similar images to the supervised data in the database can be indicated in the top order. The experimental results show that the average precision of this system becomes 11.6 % better than the conventional system.
With the development of technology for detailed examination of the vibration of the vocal cords, the use of highspeed endoscopic camera images has become widespread. Studies conducted to segment the glottis, which is ...
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ISBN:
(纸本)9781665436496
With the development of technology for detailed examination of the vibration of the vocal cords, the use of highspeed endoscopic camera images has become widespread. Studies conducted to segment the glottis, which is located between the vocal cords of particular interest, from these images use classical segmentation methods such as histogram, active contour, and region enlargement. In this study, a deep learning model was developed for glottis segmentation using the U-Net architecture, which has shown superior performance in biomedical image segmentation in recent years, and the performance of this model was developed on an IRCAM database consisting of 256x256 3000 images, which were manually labeled. It has been compared with classical segmentation methods. However, how the glottis size affects the segmentation performance was examined. As a result of the study, it was observed that system performances decreased as the glottal area size decreased, especially active contour performance decreased significantly, but this effect remained limited in the U-Net model. The developed model showed the highest performance with 0.88 sensitivity and 0.99 accuracy on average regardless of the size of the glottal area. In terms of recall, the histogram-based method yielded the highest result with 0.96. In terms of DICE, U-Net gave the best result with a score of 0.83.
In this paper, we propose a method to embed the color information of an image in a corresponding grey-level image. The objective of this work is to allow free access to the grey-level image and give color image access...
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ISBN:
(纸本)9780819466211
In this paper, we propose a method to embed the color information of an image in a corresponding grey-level image. The objective of this work is to allow free access to the grey-level image and give color image access only if you own a secret key. This method is made of three major steps which are a fast color quantization, an optimized ordering and an adapted data hiding. The principle is to build an index image which is, in the same time, a semantically intelligible grey-level image. In order to obtain this particular index image, which should be robust to data hiding, a layer running algorithm is proceeded to sort the K colors of the palette. The major contributions of this paper are the fast color quantization, the optimized layer running algorithm, the color palette compression and the adapted data hiding.
This paper deals with the problem of estimating multiple motions at points where these motions are overlaid. We present a new approach that is based on block-matching and can deal with both transparent motions and occ...
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ISBN:
(纸本)0819452114
This paper deals with the problem of estimating multiple motions at points where these motions are overlaid. We present a new approach that is based on block-matching and can deal with both transparent motions and occlusions. We derive a block-matching constraint for an arbitrary number of moving layers. We use this constraint to design a hierarchical algorithm that can distinguish between the occurrence of single, transparent, and occluded motions and can thus select the appropriate local motion model. The algorithm adapts to the amount of noise in the image sequence by use of a statistical confidence test. The algorithm is further extended to deal with very noisy images by using a regularization based on Markov Random Fields. Performance is demonstrated on image sequences synthesized from natural textures with high levels of additive dynamic noise.
Recently, efficient image coding for machines method is widely required under machine vision task-oriented coding scenarios. To achieve higher task accuracy under a certain bitrate constraint, existing solutions take ...
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In this paper, a practical real-time path planning and robot navigation algorithm for a non-holonomic indoor mobile robot based on visual servoing is implemented. The proposed algorithm is divided into three parts;the...
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ISBN:
(纸本)9781467391948
In this paper, a practical real-time path planning and robot navigation algorithm for a non-holonomic indoor mobile robot based on visual servoing is implemented. The proposed algorithm is divided into three parts;the first part uses Multi-Stencils Fast Marching (MSFM) as a path planning method. But the generated path results from fast marching methods when used directly, not guaranteed to be safe and smooth. Subsequently, the robot can touch corners, walls and obstacles. The proposed algorithm uses imageprocessing methods to solve this problem. The second part estimates the position and orientation of the robot, from the visual information, to follow the desired path with avoiding obstacles. The third part proposes a decentralized PD-like Fuzzy Logic Controller (FLC) to keep up the robot on the desired path. Experimental results show that the developed design is valid to estimate shortest-path by avoiding obstacles and able to guide the robot to follow the path in real-time.
A new soft relevance technique for scene categorization is proposed in this paper. A popular approach for scene categorization is the Bag-of-Words (BoW) framework, where a histogram is calculated for each image as the...
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