Image segmentation with pulse-coupled neural network and Canny operators

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• 作者：Wen Jiang^a ; ^bAuthor Vitae ; Haoyu Zhou^a ; ^{zhou_haoyu@163.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Yue Shen^aAuthor Vitae ; Bo Liu^aAuthor Vitae ; Zigang Fu^aAuthor Vitae
• 关键词：Image segmentation ; Color image ; Canny operators ; Pulse-coupled neural networks
• 刊名：Computers & Electrical Engineering
• 出版年：2015
• 出版时间：August 2015
• 年：2015
• 卷：46
• 期：Complete
• 页码：528-538
• 全文大小：2454 K

文摘

In this paper, a Canny operator-based method using PCNN (Pulse-Coupled Neural Network) is proposed for color image segmentation. The coarse location information of the salient object and the background is first estimated based on the distribution of the detected key-points. An image is then over-segmented into super-pixels and their histograms are computed. The saliency of a super-pixel is obtained according to the maximum of variance ration and Shannon entropy. Color image segmentation is implemented using PCNN based on Canny operator edge detection method. The proposed method is compared with state-of-the-art methods on the widely used dataset, and the experiments show that it overall obtains more accurate results.