Journal of Northeastern University Natural Science ›› 2018, Vol. 39 ›› Issue (4): 483-487.DOI: 10.12068/j.issn.1005-3026.2018.04.006

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Improved Region-Scalable Fitting Image Segmentation Method

GONG Zhao-xuan1,2, TAN Wen-jun1, GUO Wei2, ZHAO Da-zhe1,3   

  1. 1. School of Computer Science & Engineering, Northeastern University, Shenyang 110169, China; 2.School of Computing, Shenyang Aerospace University, Shenyang 110036, China; 3. Neusoft Group Co., Ltd., Shenyang 110169, China.
  • Received:2016-11-02 Revised:2016-11-02 Online:2018-04-15 Published:2018-04-10
  • Contact: ZHAO Da-zhe
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Abstract: The region-scalable fitting(RSF) model can effectively solve the problem of intensity inhomogeneities, but the traditional RSF model only considers the case where the point on the image intersects with the zero level set in its local extension area, which easily leads to over-segmentation. To solve the problem, an improved region-scalable fitting method was proposed, i.e., the case where every point in the image does not intersect with the zero level set in its extended neighborhood was considered based on the RSF model, and the value of intensity energy in this case was redefined to make the inner intensity energy and the outer intensity energy strictly equal. Experiment results showed the proposed method effectively solves the over-segmentation caused by the initialization problem.

Key words: region-scalable fitting, intensity inhomogeneities, segmentation, initialization, zero level set

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