JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (3): 58-64.doi: 10.6040/j.issn.1672-3961.1.2015.092

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Neighborhood similarity descriptor used in halftone image

ZHONG Zhiyan, WEN Zhiqiang*, ZHANG Xiaoyun, YE Degang   

  1. School of Computer &
    Communication, Hunan University of Technology, Zhuzhou 412007, Hunan, China
  • Received:2015-05-12 Online:2016-06-30 Published:2015-05-12

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Abstract: Local binary pattern was obtained by extracting local features, which was appropriate for unobvious textural features but suffered high feature dimension problem. To solve this problem, the neighborhood similarity descriptor method for halftone image feature extraction was proposed. First, the center pixel was compared with its eight neighborhood pixels. Second, the similarity index was computed for those pixel pairs. The similarity index was taken as textural feature vector after normalizing the statistics. Finally, BP neural network was adopted to classify the extracted image features in experiment. Experimental results showed that the proposed method was better than the local binary pattern algorithm in the computational complexity and recognition accuracy.

Key words: local binary pattern, halftone image, feature extraction, neighborhood similarity descriptor, center pixel

CLC Number: 

  • TP391
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