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ieee symposium on computational intelligence in image and signal processing

作者： De Bruyne, Sarah De Schrijver, Davy De Neve, Wesley Van Deursen, Davy Van de Walle, Rik Univ Ghent IBBT Dept Elect & Informat Syst Multimedia Lab B-9050 Ledeberg Ghent Belgium

ISBN: (纸本)9781424407071

Semantic video adaptation takes into account the relevance of the different fragments of the video content in order to create a tailored video stream based on the user's preferences. As a shot can be considered as the smallest semantic unit in a video sequence, metadata can be added to each shot using MPEG-7 descriptions. Based on these metadata and the user's preferences, the original bitstream can be adapted in order to obtain the desired fragments. MPEG-21 DIA offers a tool, gBS Schema, for exposing the high-level structure of a binary resource as an XML description. In this paper, shot information is inserted in these descriptions to create a link between metadata and semantic video adaptation. Furthermore, this paper proposes to keep the structure of these descriptions format-agnostic. As a result, only one generic transformation style sheet has to be implemented to support shot-based video adaptation of sequences compliant with different video specifications. Special attention is payed to sequences coded with the H.264/AVC standard as this specification contains several interesting features important for shot-based video adaptation.

关键词： image enhancement

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Dim Target Detection Based on Visual Saliency In Linear CCD image 8

Dim Target Detection Based on Visual Saliency In Linear CCD ...

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8th International symposium on computational intelligence and Design (ISCID)

作者： Li, Yajing Lei, Zhiyong Gao, Junchai Xian Technol Univ Sch Elect Informat Engn Xian Peoples R China

ISBN: (纸本)9781467395878

To solve the problem that the dim target of line-scan CCD image detection in complex background, a target detection method based on visual significance is proposed. According to the characteristics of line-scan CCD target image, a new feature vector was constructed, double search windows were designed which was similar to the target shape, and the line-scan CCD image's saliency map was got through calculating the similarity of the center and surrounding pixels neighborhoods' feature vector in the window. Then the saliency map was clustered and segmented to extract the targets. The experiment results show that the method can effectively suppress noise and background to detect dim targets in the images.

关键词： image processing Target Detection Dim Target Visual Saliency Clustering

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ADAPTIVE SMOOTHING - A GENERAL TOOL FOR EARLY VISION

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ieee TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE intelligence 1991年第6期13卷 514-529页

作者： SAINTMARC, P CHEN, JS MEDIONI, G UNIV SO CALIF INST ROBOT & INTELLIGENT SYST LOS ANGELES CA 90089 USA

We present a method to smooth a signal-whether it is an intensity image, a range image or a planar curve-while preserving discontinuities. This is achieved by repeatedly convolving the signal with a very small averaging mask weighted by a measure of the signal continuity at each point. The method is extremely attractive since edge detection can be performed after a few iterations, and features extracted from the smoothed signal are correctly localized. Hence no tracking is needed, as in Gaussian scale-space. This last property allows us to derive a new scale-space representation of a signal using the adaptive smoothing parameter k as the scale dimension. We then show how this process relates to anisotropic diffusion. When a large amount of smoothing is desired, we propose a multigrid implementation which reduces the computational time significantly. Given the local nature of the algorithm, we also propose a parallel implementation: the running time on a 16K Connection Machine is three orders of magnitude faster than on a serial machine. We then present several applications of adaptive smoothing: edge detection, range image feature extraction, corner detection, and stereo matching. Examples are given throughout the text using real images.

关键词： CORNER DETECTION EARLY processing EDGE DETECTION MULTIGRID processing RANGE image ANALYSIS REGION SEGMENTATION SMOOTHING STEREO

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Concurrent self-organizing maps for multispectral facial image recognition

Concurrent self-organizing maps for multispectral facial ima...

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ieee symposium on computational intelligence in image and signal processing

作者： Neagoe, Victor-Emil Mugioiu, Alexandru-Cristian Tudoran, Cristian-Tudor Univ Politehn Bucuresti Dept Elect Telecommun & Informat Technol Bucharest 062510 Romania

ISBN: (纸本)9781424407071

This paper is dedicated to multispectral facial recognition, based on the model of Concurrent Self-Organizing Maps (CSOM), previously proposed by first author. The first approach of this paper is to apply CSOM classifier for color face recognition. Main variant of this approach has the follwing processing stages: (a) color conversion from the 3D RGB space into an optimum 2D selected color feature space;(b) Principal Component Analysis (PCA) for each resulted color component;(c) feature fusion;(d) CSOM/SOM classification. The proposed system is experimented using the ESSEX database of color facial images;it contains 151 subjects, where each is represented by 20 pictures of 200 x 180 pixels. The obvious advantage of CSOM over SOM is proved. The second approach of this paper is the implementation of a real time CSOM face recognition system using the decision fusion that combines the recognition scores generated from visual channels M G, B, and Y classifiers) with the thermal infrared classifier. As a source of color and infrared images, we used our VICFACE database of 38 subjects. Any picture has 160 x 120 pixels;for each subject there are pictures corresponding to various face expressions and illuminations, in the visual and infrared spectrum. The spectral sensitivity of infrared images corresponds to the longwave range of 7.5 - 13 pm. The very good experimental results are given, proving nearly invariance to illumination conditions.

关键词： Face recognition

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Learning computationally Efficient Approximations of Complex image Segmentation Metrics

Learning Computationally Efficient Approximations of Complex...

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8th International symposium on image and signal processing and Analysis (ISPA)

作者： Minervini, Massimo Rusu, Cristian Tsaftaris, Sotirios A. IMT Inst Adv Studies Lucca Italy

ISBN: (纸本)9789531841948;9789531841870

image segmentation metrics have been extensively used in the literature to compare segmentation algorithms among each other, or relative to a ground-truth segmentation. Some metrics are easy to compute (e.g., Dice, Jaccard), others are more accurate (e.g., the Hausdorff distance) and may reflect local topology, but they are computationally demanding. While certain attempts have been made to create computationally efficient implementations of such complex metrics, in this paper we approach this problem from a radically different viewpoint. We construct approximations of a complex metric (e.g., the Hausdorff distance), combining a small number of computationally lightweight metrics in a linear regression model. We also consider feature selection, using sparsity inducing strategies, to restrict the number of metrics employed significantly, without penalizing the predictive power of the model. We demonstrate our methodology with image data from plant phenotyping experiments. We find that a linear model can effectively approximate the Hausdorff distance using even a few features. Our approach can find many applications, but is largely expected to benefit distributed sensing scenarios where the sensor has low computational capacity, whereas centralized processing units have higher computational capabilities.

关键词： approximation theory image segmentation learning (artificial intelligence) regression analysis topology

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A graph-based signal processing approach for low-rate energy disaggregation

A graph-based signal processing approach for low-rate energy...

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2014 ieee symposium on computational intelligence for Engineering Solutions, CIES 2014

作者： Stankovic, Vladimir Liao, Jing Stankovic, Lina Department of Electronic and Electrical Engineering University of Strathclyde GlasgowG1 1XW United Kingdom

ISBN: (纸本)9781479945108

Graph-based signal processing (GSP) is an emerging field that is based on representing a dataset using a discrete signal indexed by a graph. Inspired by the recent success of GSP in image processing and signal filtering, in this paper, we demonstrate how GSP can be applied to non-intrusive appliance load monitoring (NALM) due to smoothness of appliance load signatures. NALM refers to disaggregating total energy consumption in the house down to individual appliances used. At low sampling rates, in the order of minutes, NALM is a difficult problem, due to significant random noise, unknown base load, many household appliances that have similar power signatures, and the fact that most domestic appliances (for example, microwave, toaster), have usual operation of just over a minute. In this paper, we proposed a different NALM approach to more traditional approaches, by representing the dataset of active power signatures using a graph signal. We develop a regularization on graph approach where by maximizing smoothness of the underlying graph signal, we are able to perform disaggregation. Simulation results using publicly available REDD dataset demonstrate potential of the GSP for energy disaggregation and competitive performance with respect to more complex Hidden Markov Model-based approaches. © 2014 ieee.

关键词： Domestic appliances

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A Real-time and High-efficiency Surface Defect Detection Method for Metal Sheets Based on Compact CNN 13

A Real-time and High-efficiency Surface Defect Detection Met...

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13th International symposium on computational intelligence and Design (ISCID)

作者： Zhou, Xinyue Nie, Yuman Wang, Yaoxiong Cao, Pingguo Ye, Ming Tang, Yuanyang Wang, Zhou Chinese Acad Sci Hefei Inst Phys Sci Hefei Peoples R China Univ Sci & Technol China Hefei Peoples R China

ISBN: (纸本)9781728184463

Surface defect detection has received increased attention in the quality control of industrial products. It is an urge need to develop a real-time, high-efficiency defect detection algorithm on automatic detection equipment. The traditional image processing method based on connected domain does not meet the throughput requirement and cost huge efforts. In this paper, A novel detection algorithm based on compact convolutional neural network (CNN) is applied to confirm the defect's existence in the target region of an image. Experimental results show that our proposed compact CNN detection kernel finishes in 7ms per image and it achieves 8.57x speedup when compared to the traditional image processing method. Our compact CNN-based real-time processing pipeline also achieves 96.85% detection accuracy rate, which is more accurate and robust than human detection and traditional image processing algorithms. For the whole image processing pipeline, it achieves 1.79x throughput improvement in terms of image per second and higher efficiency in terms of out-of-pocket cost.

关键词： surface defect detection deep learning CNN image processing

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An Embedded image processing System Based on WinCE

An Embedded Image Processing System Based on WinCE

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2nd International symposium on computational intelligence and Design

作者： Pang, Zhifeng Yang, Huili Gao, Guilong Hebei Univ Sci & Technol Coll Informat Sci & Engn Shijiazhuang Peoples R China

ISBN: (纸本)9780769538655

Aim at the demand for real-time and miniaturization of present image processing system, we designed an embedded image processing system which used ARM9 for microprocessor. The system designed in this paper is based on the processor of S3C2410 and the Windows CE operating system, and completed the work of programming in EVC. The system integrates all the functions of image capturing, processing and displaying, and takes on the character of low cost and good adaptation, especially suitable for the image processing application system which required strictly to consumed power and cubage.

关键词： Embedded S3C2410 image processing WinCE

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Parallel Implementation of OpenVX on Firefly2 GPU 8

Parallel Implementation of OpenVX on Firefly2 GPU

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8th International symposium on computational intelligence and Design (ISCID)

作者： Guo, Zhiquan Han, Jun Gang Che, Fang Li, Tao Xian Univ Posts & Telecommun Sch Comp Sci Xian Peoples R China Xian Univ Posts & Telecommun Sch Elect Engn Xian Peoples R China

ISBN: (纸本)9781467395878

Given the fact that the traditional GPU mainly supports the parallel computing with SIMD (Single Instruction Multiple Data) and SIMT (Single Instruction Multiple Thread) mode, the Firefly2 GPU (Graphic processing Unit) has special hardware configuration mechanism and can be used for paralleling computing on data-level, thread-level and operatedlevel. This paper presents parallel implementation of OpenVX kernels on Firefly2 GPU with the method by combing the operation level parallelism with data level parallelism. Experimental results indicate satisfactory speedup of the parallel implementation and show that the Firefly2 is suitable for graphics and image processing.

关键词： GPU OpenVX parallel image processing

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Research on Case Representation Method Based on image Information

Research on Case Representation Method Based on Image Inform...

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6th International symposium on computational intelligence and Design (ISCID)

作者： Li Hongru He Xiaochen Zhao Yubin Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China

ISBN: (纸本)9780769550794

According to the fact that it's more likely to consider the image as the field of knowledge, and the image has the features of intuitivism, ample content, no language limited and convenient for communicating internationally, this article use the case-based reasoning method to decrease the difficulty of obtaining the knowledge, and then propose the case representation method based on image information. We have studied the RGB color model and HSV color model, and then discuss the conversion formula between them. What's more, we have studied the method of extracting the image color characteristics as image case attributes' description, make a model of image case, and then make a case representation on the forest fire early warning image.

关键词： image Information CBR Case Representation image processing

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