Microscopic Local Binary Pattern for Texture Classification
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概要
- 論文の詳細を見る
This paper presents a Microscopic Local Binary Pattern (MLBP) for texture classification. The conventional LBP methods which rely on the uniform patterns discard some texture information by merging the nonuniform patterns. MLBP preserves the information by classifying the nonuniform patterns using the structure similarity at microscopic level. First, the nonuniform patterns are classified into three groups using the macroscopic information. Second, the three groups are individually divided into several subgroups based on the microscopic structure information. The experiments show that MLBP achieves a better result compared with the other LBP related methods.
- The Institute of Electronics, Information and Communication Engineersの論文
- 2012-09-01
著者
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HE Jiangping
the Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University
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YANG Xin
the Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University
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SONG Wei
the Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University
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JI Hongwei
the Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University