Journal of South China University of Technology (Natural Science Edition) ›› 2013, Vol. 41 ›› Issue (2): 12-18.doi: 10.3969/j.issn.1000-565X.2013.02.003

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

Disparity Estimation Algorithm Based on Color Segmentation and Graph Cut Algorithm

Yuan Hui1 Li Zhi-bin2 Liu Wei3   

  1. 1. School of Information Science and Engineering, Shandong University, Ji'nan 250100, Shandong, China; 2. Research Laboratory of Internet of Things, National Telecommunication Metrology Center of the Ministry of Industry and Information Technology, Beijing 100191, China; 3. Qingdao Hisense State Key Laboratory of Digital Multi-Media Technology, Qingdao 266061, Shandong, China
  • Received:2012-06-25 Revised:2012-11-07 Online:2013-02-25 Published:2013-01-05
  • Contact: 元辉(1984-),男,博士,讲师,主要从事多媒体通信研究. E-mail:huiyuan@sdu.edu.cn
  • About author:元辉(1984-),男,博士,讲师,主要从事多媒体通信研究.
  • Supported by:

    国家"973"计划项目(2009CB320905,2010CB735906);国家自然科学基金资助项目(61201211);教育部博士点基金资助项目(20120131120032);山东省优秀中青年科学家奖励基金资助项目(BS2012DX021);中国博士后科学基金特别资助项目(2012T50629);中国博士后科学基金面上项目(2011M501131,2011M501092);山东省博士后创新项目专项资金资助项目(201203053);山东大学自主创新基金资助项目(2010JC007,2011GN061)

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Abstract:

In order to improve the accuracy of disparity estimation, an algorithm based on color segmentation and graph cut algorithm is proposed. In this algorithm, the current image is segmented into several color areas by em-ploying the mean shift algorithm, and the graph cut is implemented on the pixel set of each color area to allocate disparities for the pixels in the color area. Unlike the traditional global optimization algorithm, the proposed algo-rithm takes the pixel set of a color area rather than the whole image as an entirety to perform the global optimiza-tion, thus improving the disparity accuracy of object boundaries. Experimental results demonstrate that the proposed algorithm is more effective than the traditional one.

Key words: graph cut, color segmentation, global optimization, disparity estimation, mean shift

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