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Titlebook: Computer Analysis of Images and Patterns; 8th International Co Franc Solina,Ale?s Leonardis Conference proceedings 1999 Springer-Verlag Ber

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書目名稱Computer Analysis of Images and Patterns
副標(biāo)題8th International Co
編輯Franc Solina,Ale?s Leonardis
視頻videohttp://file.papertrans.cn/234/233435/233435.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computer Analysis of Images and Patterns; 8th International Co Franc Solina,Ale?s Leonardis Conference proceedings 1999 Springer-Verlag Ber
描述This volume presents the articles accepted for the 8th International Conference on Computer Analysis of Images and Patterns (CAIP’99), held in Ljubljana, Slovenia, 1{3 September 1999. The CAIP series of conferences started 14 years ago in Berlin. The series served initially as a forum for meetings between sci- tists from Western and Eastern-bloc countries. Political circumstances have changed dramatically since the inception of the conference and such contacts are fortunately no longer subject to abstrade. While CAIP conferences are still rooted in Central Europe, they now attract participants from all over the world. We received 120 submissions, which went through a thorough double blind review process by the program committee members who, had the option of - signing additional reviewers. The nal program consists of 47 oral and 27 poster presentations, with authors from 25 di erent countries. The proceedings also include 2 of the 5 invited lectures given at the conference. In the name of the steering committee we would like to thank the program committee members and the additional reviewers for their time and e orts. Our thanks also go to the authors for their cooperation and meet
出版日期Conference proceedings 1999
關(guān)鍵詞3D; Stereo; classification; construction; databases; image compression; image processing; image registratio
版次1
doihttps://doi.org/10.1007/3-540-48375-6
isbn_softcover978-3-540-66366-9
isbn_ebook978-3-540-48375-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 1999
The information of publication is updating

書目名稱Computer Analysis of Images and Patterns影響因子(影響力)




書目名稱Computer Analysis of Images and Patterns影響因子(影響力)學(xué)科排名




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書目名稱Computer Analysis of Images and Patterns網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computer Analysis of Images and Patterns被引頻次




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MCEBC — A Blob Coloring Algorithm for Content-Based Image Retrieval Systemuantized colors for various reasons. In some systems, especially the systems accepting user-drawn queries, color quantization improves the overall performance as well as the execution time. In this paper, a new color quantization method, which uses some heuristics to minimize the color matching erro
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EigenHistograms: Using Low Dimensional Models of Color Distribution for Real Time Object Recognitionocused on defining optimal spaces for representing pixel values that are related to physical models and that present some invariance. We propose a new approach to identify individual object color distributions by using statistical learning techniques and to allow their compact representation in low
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A Novel Approach to the 2D Analytic Signalis not possible by a straightforward extension of the 1D definition. There rather occur several different approaches in the literature. We review the main approaches and propose a new definition which is based on the recently introduced quaternionic Fourier transform. The approach most closely relat
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Edge Preserving Probabilistic Smoothing Algorithmicle performing a random walk on the image lattice, with transition probabilities derived from the median distribution. The probabilistic smoothing algorithm combined with a cooling procedure, known from the simulated annealing optimization method, constitutes a new powerful technique of noise suppr
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FORI-CSDR - A New Approach for Context Sensitive Image Data Reductions able to reduce the amount of image data in dependence of the image context. Within the important image regions nearly no image data will be reduced. The image data of the unimportant image regions are reduced in a very strong way. The data reduction factors for the important and the unimportant im
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