吉林大学学报(工学版) ›› 2017, Vol. 47 ›› Issue (1): 255-261.doi: 10.13229/j.cnki.jdxbgxb201701037

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Multi-scale 3D Otsu thresholding algorithm based on Gaussian decomposition

XIAO Ming-yao1, 2, LI Xiong-fei2   

  1. 1.College of Computer Science and Technology, Changchun Normal University, Changchun 130032, China;
    2.College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Received:2016-02-22 Online:2017-01-20 Published:2017-01-20

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Abstract: Current thresholding algorithms for image segmentation are sensitive to noise. To overcome this problem, a new Otsu thresholding algorithm is proposed based on image decomposition. The whole segmentation algorithm is designed as an iteration procedure. In each iteration the image is segmented by the 3D Ostu, and then it is filtered by Gaussian kernel filtering to get a smoothed image, which is taken as the input of the next iteration. Finally, segmentation results obtained in the iterations and are pooled to get final segmentation. The advantages of the proposed algorithm are that its segmentation results are stable and it is robust to noise. Experiments on medical MR brain images are conducted to demonstrate the effectiveness of the proposed method. Results indicate that the proposed algorithm is superior to other thresholding algorithms.

Key words: computer application, image segmentation, Otsu algorithm, noises, Gaussian decomposition

CLC Number: 

  • TP391
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