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Multichannel Pulse-Coupled-Neural-Network-Based Color Image Segmentation for Object Detection

【摘要】 This paper proposes a pulse-coupled neural network (PCNN) with multichannel (MPCNN) linking and feeding fields for color image segmentation. Different from the conventional PCNN, pulse-based radial basis function units are introduced into the model neurons of PCNN to determine the fast links among neurons with respect to their spectral feature vectors and spatial proximity. The computing of the color image segmentation can be implemented in parallel on a field-programmable-gate-array chip. Furthermore, the results of segmentations are applied to an object-detection scheme. Experimental results show that the performance of the proposed MPCNN is comparable to those of other popular image segmentation algorithms for the segmentation of noisy images while its parallel neural circuits improve the speed of processing drastically as compared with the sequential-code-based counterparts.

【期刊名称】 Industrial Electronics, IEEE Transactions on

【作者】 Hualiang Zhuang;

【作者单位】

【收录信息】

【年(卷),期】2012(59),8

【年度】2012

【页码】p.3299-3308

【总页数】10

【原文格式】PDF

【正文语种】eng

【中图分类】

【原文服务方】国家工程技术数字图书馆

【关键词】

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