MATLAB code and data for our paper:
Automatic image thresholding using Otsu’s method and entropy weighting scheme for surface defect detection
M. T. N. Truong and S. Kim
Journal of Soft Computing, vol. 22, no. 13, pp. 4197–4203, 2018
https://link.springer.com/article/10.1007/s00500-017-2709-1
Besides the implementation of our proposed method, we also provide our implementations of several thresholding methods which were used for comparison in our paper.
entropy_otsu.m: Our method.my_otsu.m: Our implementation of Otsu's method.valley_emphasis.m: H. F. Ng. Automatic thresholding for defect detection. Pattern Recognition Letters, 27(14):1644-1649, 2006.neighbor_valley_emphasis.m: J. L. Fan and B. Lei. A modified valley-emphasis method for automatic thresholding. Pattern Recognition Letters, 33(6):703-708, 2012.gaussian_valley_emphasis.m: H. F. Ng, D. Jargalsaikhan, H. C. Tsai, and C. Y. Lin. An improved method for image thresholding based on the valley-emphasis method. In Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2013 Asia-Pacific, pages 1-4, Kaohsiung, Taiwan, 2013. IEEE.lda_valley_emphasis.m: Z. Liu, J. Wang, Q. Zhao, and C. Li. A fabric defect detection algorithm based on improved valley-emphasis method. Research Journal of Applied Sciences, Engineering and Technology, 7(12):2427-2431, 2014.main_script.m: This source code reproduces two tables in our publication.
Ten samples of wafer surface used in experiments.