吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (2): 528-534.doi: 10.13229/j.cnki.jdxbgxb201602030

• Orginal Article • Previous Articles     Next Articles

Fast recursive multi-thresholding algorithm

SHEN Xuan-jing1, 2, ZHANG He1, 2, CHEN Hai-peng1, 2, WANG Yu1, 2, 3   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012, China;
    2.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China;
    3.College of Applied Technology,Jilin University, Changchun 130012, China
  • Received:2014-07-20 Online:2016-02-20 Published:2016-02-20

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Abstract: The Neighborhood Valley-emphasis method can not get the right threshold value in some cases, such as the valley feature between the target and background is not very distinct. In order to solve this problem, a global thresholding method is proposed. This method is based on the gray information around the valley-point neighborhood and the relative characteristics between the valley point and its adjacent crest-point. The proposed method weights the objective function with the gray information around the valley-point neighborhood and the relation between the valley-point and its adjacent crest-point. It improves the accuracy of the threshold obtained by OTSU. The optimal threshold got by the proposed method has less valley-to-crest ratio. In other word, the valley gray is taken as the optimal threshold, which has larger height difference with it adjacent crest-point. In order to improve the efficiency, a recursive single threshold method based on the aforesaid algorithm is used to achieve the image multi-threshold segmentation. Experiment results show that the proposed method has great segmentation performance and low time complexity.

Key words: computer application, image segmentation, multilevel thresholding, recursion, OTSU method, valley point

CLC Number: 

  • TP391
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