• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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Fast object extraction using human-machine
interactive graph cuts

XU Qiu-ping   

  1. (School of Information Engineering,Engineering University of Armed Police Force,Xi’an 710086,China)
  • Received:2019-04-03 Revised:2019-08-29 Online:2020-02-25 Published:2020-02-25

Abstract:

By characterizing pixel distance with RGB pixel value, based on graph cuts theory, an human-machine interactive fast object extraction method is proposed. Closed polygons are artificially drawn around the object as the initial contour line, a single-side variable width cyclic neighborhood is generated to avoid ineffective overlapping and repeated cutting. Meantime, an energy function is constructed and a s-t network is generated to achieve the object extraction through the minimus cost cutting of the s-t network. Repeat the above steps until converge to the best boundary of the object. Later, convenient, fast, safety-oriented, automatic and manual error correction measures are provided for local errors. Experiments show that method has the advantages of convenient human-machine interaction, efficient and complete error correction, and fast and accurate object extraction.
 

Key words: object extraction, image segmentation, graph cuts, human-machine interaction