J4 ›› 2011, Vol. 38 ›› Issue (5): 52-58+183.doi: 10.3969/j.issn.1001-2400.2011.05.009

• Original Articles • Previous Articles     Next Articles

Classification and recognition algorithm for the halftone image

KONG Yueping1,3;ZENG Ping2;ZHANG Yuepeng3   

  1. (1. School of Info. and Control, Xi’an Univ. of Architecture and Tech., Xi’an  710055,China;
    2. Research Inst. of Computer Peripherals, Xidian Univ., Xi'an  710071, China;
    3. Xi'an Research Inst. of Survey and Mapping, Xi'an  710054, China)
  • Received:2010-06-24 Online:2011-10-20 Published:2012-01-14
  • Contact: KONG Yueping E-mail:annie_kyp@sina.com

Abstract:

After analyzing the influences of quality on inverse halftoning, the research on how to classify the halftone has gone into our view. Using the Self-correlation Function of one-dimension, the Grey Level Co-ocurrence Matrices(GLCM) and the Grey Run-length Matrices(GLRM) the periodic and texture features of the halftoning image are discovered. Based on these properties a new classification algorithm for usual halftones is proposed. Experimental results indicate that the average rate of correct recognition has reached 99%. The new algorithm not only solves the application problem for Estimated-Inverse-Halftoning, but also makes a basic of design and optimization for inverse halftoning.

Key words: halftoning image, image feature, image classification

CLC Number: 

  • TN911.73