期刊
PATTERN RECOGNITION
卷 41, 期 1, 页码 117-129出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2007.03.029
关键词
Parzen window; thresholding; image segmentation
Image segmentation is one of the most important and fundamental tasks in image processing and techniques based on image thresholding are typically simple and computationally efficient. However, the image segmentation results depend heavily on the chosen image thresholding methods. In this paper, histogram is integrated with the Parzen window technique to estimate the spatial probability distribution of gray-level image values, and a novel criterion function is designed. By optimizing the criterion function, an optimal global threshold is obtained. The experimental results for synthetic real-world and images demonstrate the success of the proposed image thresholding method, as compared with the OTSU method, the MET method and the entropy-based method. (C) 2007 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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