Journal of South China University of Technology (Natural Science Edition) ›› 2013, Vol. 41 ›› Issue (11): 8-15,22.doi: 10.3969/j.issn.1000-565X.2013.11.002

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Improved Corner Detection Based on Multi- Direction Latticed Differential and Competitive Suppression

Ma Li- hong1 Li Jian- hui1 Tan Xing- jun2   

  1. 1.School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China;2.Department of Network Architecture and System Design,HiSilicon Technologies Co.,Ltd.,Shenzhen 518129,Guangdong,China
  • Received:2013-05-21 Revised:2013-07-11 Online:2013-11-25 Published:2013-10-11
  • Contact: 马丽红(1965-)，女，博士，教授，主要从事图像视频信号处理、容错编码和数据隐藏、模式识别研究． E-mail:eelhma@scut.edu.cn
  • About author:马丽红(1965-)，女，博士，教授，主要从事图像视频信号处理、容错编码和数据隐藏、模式识别研究．
  • Supported by:

    国家自然科学基金资助项目(60972133)

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Abstract:

A multi- direction latticed differential (DLD) operator combined with the“Winner Takes All (WTA)”competitive suppression strategy is proposed to remove the false corners along zigzag image edges and the repeatedly-detected corners in smooth regions,which improves the performance of the corner detector.In the investigation,first,a differential operator based on the Directionlet decomposition is proposed to eliminate the zigzag distortion.With the multi- direction latticed complex representation of the operator,image edges in arbitrary direction can bedenoted without zigzag,and false corners with zigzag appearance can be effectively suppressed.Then,a competitivesuppression algorithm,which defines a corner similarity with the constraint of neighborhood size according to theDLD response value,and merges similar corners with the WTA strategy,is put forward to remove slowly- varyingcorners.Experimental results show that the typical GLCP detector and the FAST detector combined with DLD areboth obviously improved.For instance,the ACU value,which is a comprehensive evaluation index of the error de-tection rate and the missed detection rate,increases by 12.14% and 6.32%,respectively.

Key words: corner detection, latticed differential, competitive suppression, Directionlet decomposition, false corner, Winner Takes All

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