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5th international symposium on multispectral image processing and pattern recognition

作者： Xiang, HaiLin Sun, Qiang Jiao, LiCheng Xidian Univ Inst Elect Engn Xian 710071 Peoples R China

ISBN: (纸本)9780819469502

A supervised multiscale image segmentation method is presented based on one class support vector machine (OCSVM) and wavelet transformation. Wavelet coefficients of training images in the same directions at different scale are organized into tree-type data as training samples for OCSVMs. Likelihood probabilities for observations of segmentation image can be obtained from trained OCSVMs. Maximum likelihood classification is used for image raw segmentation. Bayesian rule is then used for pixel level segmentation by fusing raw segmentation result. In experiments, synthetic mosaic image, aerial image and SAR image were selected to evaluate the performance of the method, and the segmentation results were compared with presented hidden Markov tree segmentation method based on EM algorithm. For synthetic mosaic texture images, miss-classed probability was given as the evaluation to segmentation result. the experiment showed the method has better segmentation performance and more flexibility in real application compared with wavelet hidden Markov tree segmentation.

关键词： wavelet one class support vector machine Bayesian decision image segmentation multiresolution

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Moving point target trajectory detection based on dual-Hough transform

Moving point target trajectory detection based on dual-Hough...

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5th international symposium on multispectral image processing and pattern recognition

作者： Hu, Jing Zhang, Tian-Xu Inst Pattern Recognit Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Educ Minist Image Proc & Intelligent Cont Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469502

this paper deals with research on detecting moving point target trajectory in image sequence. A novel method is presents for this purpose, which combines two 2-dimension Hough transforms to suppress noise points and to detect trajectory points in time order. the first Hough transform has an accumulators array using a restricted voting process and a set of straight lines are found in the image plane. A new T-L parameter space is proposed which is derived from these straight lines. In the second transform, collinear points are mapped into T-L space and it is easy to find the direction of motion. Experimental results show that our method can effectively extract moving point target trajectory accurately in a limited observing time especially scanning images from large numbers of noise points while search region is much larger than target movability.

关键词： moving point target (MPT) trajectory detection dual-Hough transform (DHT) X-Y-T observation space T-L parameter space

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Application of image processing techniques in computer graphics algorithms

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COMPUTER NETWORKS AND ISDN SYSTEMS 1997年第14期29卷 1705-1714页

作者： Rokita, P Institute of Computer Science Warsaw University of Technology ul. Nowowiejska 15/19 00-665 Warsaw Poland

image processing is usually associated with pattern recognition and is rather treated as a subject outside of the computer graphics interest. Basically computer graphics algorithms are used for the visualization of scenes or models described using some abstract notation, while image processing is used on the opposite way -i.e. when finding an abstract description of an analyzed pattern. this paper proposes to use the image processing approach for rendering optical effects in computer graphics algorithms. Proposed algorithms can be used for the generation of realistic and artistic optical effects in real-time, in, for example, visual simulators, virtual reality or multi-media applications. (C) 1997 Elsevier Science B.V.

关键词： visual simulators real time rendering image processing rendering optical phenomena convolution

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Study on edge extraction methods of the droplet image profile

Study on edge extraction methods of the droplet image profil...

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5th international symposium on multispectral image processing and pattern recognition

作者： Song, Qing Zhu, Sijia Yan, Han Wu, Wenqian Beijing Univ Posts & Telecommun Automat Sch Beijing 100876 Peoples R China

ISBN: (纸本)9780819469502

It is a key technology to detect the edge of the droplet profile exactly for application in drop volume calculation, liquid target identification and liquid characteristics analysis. the droplet images in various stages during the drop growth are firstly acquired and stored real-timely through ICCD. After a series of preprocessing, including image cutting, noise filtering, image segmentation and filling, a proper edge detection method is chosen to extract the droplet image profile. the principle and algorithm of some classical and newly developed methods for edge detection are introduced and compared in detail, such as differential operator, Laplacian operator, improved Canny operator, wavelet transformation, mathematical morphology, fuzzy operator and fractal geometry. Wavelet transformation can be used effectively for extracting the droplet image profile, because of its advantages of multiple resolution, focus variation and edge enhancement. the image records of the droplet formation and the detected profile curves are presented.

关键词： edge extraction image process droplet profile

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PCA-based visualization of terahertz time-domain spectroscopy image

PCA-based visualization of terahertz time-domain spectroscop...

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5th international symposium on multispectral image processing and pattern recognition

作者： Pei, Jihong Hu, Yong Xie, Weixin Shenzhen Univ Intelligent Informat Inst Shenzhen 518060 Peoples R China

ISBN: (纸本)9780819469519

A novel visualization method of terahertz time-domain spectroscopy (thz-TDS) image is presented, which is based on principal component analysis (PCA) technique. the proposed method include three processing steps: firstly, the thz-TDS image is preprocessed using a spatial vector filtering technique to denoise. Secondly, the thz-TDS image is transformed from spatio-temporal domain to spatio-spectral domain, and the transformed image can be viewed as a multispectral image whose spectral dimensionality D is equal to the sampled number of thz-TDS pulse at each pixel. thirdly, each of spectrum vector at a pixel is viewed as a point in D dimensional space, the covariance matrix of pixels can be computed, and then three eigenvectors corresponding to the first 3 largest eigenvalues are found by PCA technique. the thz-TDS image is projected along these three eigenvectors. By normalizing these 3 principal component images and mapping them into the RGB space, we can get a synthetic color image as a visualization result of the thz-TDS image. Due to vector-based dimensionality reduction, the proposed method can provide more visual information of the thz-TDS image than scalar-based visualization techniques. Finally, experimental results are provided to demonstrate the performance of the proposed method.

关键词： terahertz time-domain spectroscopy thz-TDS image PCA visualization dimensionality reduction

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Segmentation-based reflectance recovery

Segmentation-based reflectance recovery

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5th international symposium on multispectral image processing and pattern recognition

作者： Wu, Xiangyang Zhang, Hongxin Hangzhou Dianzi Univ Inst Graph & Image Hangzhou 310018 Peoples R China Zhejiang Univ State Key Lab CAD & CG Hangzhou 310027 Peoples R China

ISBN: (纸本)9780819469502

the reflectance properties of a surface are an essential factor in its appearance. Much previous work has focused on the problem of reflectance recovery from images. these methods must assume an a priori grouping of pixels into uniform-reflectance regions. In this paper we presented a method for automatic grouping of pixels for reflectance estimation. First a over-segmentation is achieved by traditional image segmentation. For each image region of the over-segmentation, a probability distribution is built and a reflectance subspace is formed by likelihood thresholding. the regions with the same reflectance are then merged by adapting a traditional bayesian formulation for image segmentation to increase estimation accuacy. After completing the merging process, reflectance parameter estimates are computed for the remaining subspaces by the maximum likelihood reflectance estimate. the experiment results on a synthetic scene and a real scene show our method can achieve a more accurate image segmentation and reflectance estimation than traditional methods.

关键词： image segmentation reflectance Bayesian estimation

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Multi-object segmentation algorithm based on improved Chan-Vese model

Multi-object segmentation algorithm based on improved Chan-V...

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5th international symposium on multispectral image processing and pattern recognition

作者： Fu, Xiaowei Ding, Mingyue Zhou, Chengping Cai, Chao Huazhong Univ Sci & Technol State Key Lab Multispectral Informat Proc Technol Inst Pattern Rocognit & Artificial Intelligence Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469502

Because Chan and Vese(C-V) model using one level set function can only represent one object and one background, it cannot represent multiple junctions of multiple objects. In this paper, an improved multi-object segment algorithm is proposed based on C-V model of single level set. First, the given image resolution is deduced by wavelet transform. Since the low resolution approximate image contains less noise and pixels, it can speed up the active contour evolution. Secondly, an improved C-V model of a single level set is introduced to obtain the multi-objects' approximate contour, which can make use of topology split information of the contour effectively. thirdly, the inverse discrete wavelet transform is used to the resulted image and level set of the coarse scale image, which can get the approximation contour on the original image. Lastly, the approximation contour is taken as an initial level set function and the second active contour evolution is performed on the original image to get the real multi-objects contour. Experimental results show that the proposed algorithm can realize the multi-object segmentation effectively and quickly.

关键词： image segmentation C-V model partial differential equations active contours model single level set

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Adaptive four windows wavelet image denoising based on local polynomial approximation-intersection of confidence intervals - art. no. 67862H

Adaptive four windows wavelet image denoising based on local...

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5th international symposium on multispectral image processing and pattern recognition

作者： Feng, Hongxiao Hou, Biao Jiao, Licheng Li, Haigang Xidian Univ Inst Intelligent Informat Proc Xian 710071 Peoples R China

ISBN: (纸本)9780819469502

Local Polynomial Approximation-Intersection of Confidence Intervals (LPA-ICI) is a new approach, which can find the boundary of the isotropic region efficiently, especially for noisy images. this paper presents a novel image denoising method, adaptive four windows wavelet image denoising based on LPA-ICI, which is composed of three parts: searching for four adaptive windows with LPA-ICI, updating the noisy wavelet coefficients by hard threshold and obtaining a final "clean" pixel value by fusing the updated pixels with different weights which are determined by the sparsity of regions. Experiments show that our algorithm has advanced performance, reconstructed edges are clean, and especially without unpleasant ringing artifacts.

关键词： image denoising adaptive window Local Polynomial Approximation-Intersection of Confidence Intervals weighting according to sparsity

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A reference point detection algorithm for top-view finger image recognition

A reference point detection algorithm for top-view finger im...

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5th international symposium on image and Signal processing and Analysis

作者： Chaikan, Panyayot Karnjanadecha, Montri Prince Songkla Univ Fac Engn Dept Comp Engn Songkhla Thailand

ISBN: (纸本)9789531841160

this paper describes an algorithm for automatic reference point detection in a top-view finger image recognition system. In tests of 700 finger images, only 6 images were rejected by our algorithm. A reference point location error correction technique was developed to improve the recognition accuracy. When using the proposed algorithm, the accuracy of the top-view finger image identification system was only reduced to 93.80% compared to 96.57% when using a manually defined reference point. this shows the feasibility of using top-view finger images to increase the recognition accuracy of fingerprint identification.

关键词： Error correction

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Automated airport targets detection and location based on radar imagery

Automated airport targets detection and location based on ra...

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5th international symposium on multispectral image processing and pattern recognition

作者： Shao, Yongshe Chen, Ying Li, Jing Tongji Univ Survey Dept 1239 Si Ping Rd Shanghai 200092 Peoples R China Xian Res Inst Surveying & Mapping Xian 710002 Peoples R China

ISBN: (纸本)9780819469502

Because of the influence of speckle noise, it is difficult to extract the edge of the targets and locate the airport automatically in the low SNR real aperture radar imagery by the traditional ways. the paper presents a kind of algorithms that could improve the dependability of the image matching and locate the airport target in the real aperture radar images. At first, the original real aperture radar imagery is enhanced on fuzzy property domain, which makes the airport target more prominent. then, the airport runway is detected using the Radon transform, and the end points and width of the airport runway are identified using the correlative knowledge of the airport. At last, the airport runway extracted is processed and the airport target is located with the wavelet transform and the least square image matching. the experiment shows that the method could detect and locate the airport target well.

关键词： real aperture radar image Synthetical aperture radar image Radon transform Fuzzy domain image matching and location

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