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检索条件"机构=Pattern Recognition and Image Analysis Lab"
24 条 记 录,以下是21-30 订阅
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A geometric approach for accurate and efficient performance evaluation of layout analysis methods
A geometric approach for accurate and efficient performance ...
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International Conference on pattern recognition
作者: D. Bridson A. Antonacopoulos Pattern Recognition and Image Analysis (PRImA) Research Lab School of ComputingScience and Engineering University of Sanford Greater Manchester UK Pattern Recognition and Image Analysis (PRImA) University of Salford Greater Manchester United Kingdom
A major component of performance evaluation of layout analysis methods is the comparison of ground truth regions with regions resulting from segmentation methods. The description of document regions must be both accur... 详细信息
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Page Segmentation Competition
Page Segmentation Competition
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International Conference on Document analysis and recognition
作者: A. Antonacopoulos B. Gatos D. Bridson Pattern Recognition and Image Analysis (PRImA) Research Lab School of Computing Science and Engineering University of Sanford Manchester UK Computational Intelligence Laboratory Institute of Informatics and Telecommunications National Center for Scientific Research Demokritos Athens Greece
This paper continues the authors' attempt to address the need for objective comparative evaluation of layout analysis methods in realistic circumstances. It describes the Page Segmentation Competition (modus opera... 详细信息
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Handwriting Segmentation Contest
Handwriting Segmentation Contest
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International Conference on Document analysis and recognition
作者: B. Gatos A. Antonacopoulos N. Stamatopoulos Computational Intelligence Laboratory Institute of Informatics and Telecommunications National Center for Scientific Research Demokritos Athens Greece Pattern Recognition and Image Analysis (PRImA) Research Lab School of Computing Science and Engineering University of Sanford Manchester UK
This paper presents the results of the handwriting segmentation contest that was organized in the context of ICDAR2007. The aim of this contest was to use well established evaluation practices and procedures in order ...
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Remote sensing image compression for deep space based on region of interest
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Journal of Harbin Institute of Technology(New Series) 2003年 第3期10卷 300-303页
作者: 王振华 吴伟仁 田玉龙 田金文 柳健 Institute for Pattern Recognition and Artificial Intelligence State Key Lab for Image Processing and Intelligent ControlHuazhong University of Science and Technology Wuhan 430074 China Institute for Pattern Recognition and Artificial Intelligence State Key Lab for Image Processing and Intelligent ControlHuazhong University of Science and Technology Wuhan 430074 China major limitation for deep space communication is the limited bandwidths available. The downlink rate using X-band with an L2 halo orbit is estimated to be of only 5.35 GB/d. However the Next Generation Space Telescope (NGST) will produce about 600 GB/d. Clearly the volume of data to downlink must be reduced by at least a factor of 100. One of the resolutions is to encode the data using very low bit rate image compression techniques. An very low bit rate image compression method based on region of interest(ROI) has been proposed for deep space image. The conventional image compression algorithms which encode the original data without any data analysis can maintain very good details and haven't high compression rate while the modern image compressions with semantic organization can have high compression rate even to be hundred and can't maintain too much details. The algorithms based on region of interest inheriting from the two previews algorithms have good semantic features and high fidelity and is therefore suitable for applications at a low bit rate. The proposed method extracts the region of interest by texture analysis after wavelet transform and gains optimal local quality with bit rate control. The Result shows that our method can maintain more details in ROI than general image compression algorithm(SPIHT) under the condition of sacrificing the quality of other uninterested areas
A major limitation for deep space communication is the limited bandwidths available. The downlinkrate using X-band with an L2 halo orbit is estimated to be of only 5.35 GB/d. However, the Next GenerationSpace Telescop... 详细信息
来源: 评论