Acta Photonica Sinica, Volume. 43, Issue 6, 610001(2014)
Medianbased Square Distance Symmetrical Cooccurrence Matrix Thresholding Method
The image threshold selection of skew and heavytailed classconditional distributions were studied. Due to the deviation of the meanbased method in classification estimation, the medianbased method is more reasonable in threshold selection. Based on the square distance symmetrical cooccurrence matrix, the region median was defined, and then using median classified statistics method, a new threshold approach was proposed based on the square distance symmetrical cooccurrence matrix, and the multithreshold segmentation algorithms was advanced. Compared with Otsu′s and square distance, the proposed method not only has prominent segmentation performance for the images of skew and heavytailed classconditional distributions, but it takes the more spatial statistical information on account, compared with medianbased Otsu′s thresholding, the extracted object information is more complete, and the edge is clearer. For the small object probability distribution images, this method also has better threshold segmentation effect. To illustrate the correctness and effectiveness, based on the groundtruth images, the misclassification error results show that the proposed method can obtain the minimum value.
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ZHANG Hong, FAN Jiulun. Medianbased Square Distance Symmetrical Cooccurrence Matrix Thresholding Method[J]. Acta Photonica Sinica, 2014, 43(6): 610001
Received: Sep. 9, 2013
Accepted: --
Published Online: Aug. 18, 2014
The Author Email: Hong ZHANG (zhmlsa@xupt.edu.cn)