NDLI: Robust Image Segmentation Using Pulse-coupled neural network with De-noising by Kernel PCA

Content Provider	IEEE Xplore Digital Library
Author	Jiexin Pu Hongyi Zhang Haichao Zhang Wang, Y.
Copyright Year	2006
Description	Author affiliation: Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan (Jiexin Pu)
Abstract	An image segmentation algorithm based on pulse-coupled neural network with de-noising by kernel principal component analysis (PCA) is presented in this paper. PCA enables us to extract nonlinear features and therefore performs as a powerful preprocessing step for classification. But the extracted feature components are sensitive to outliers contained in data. This is a characteristic common to all PCA-based techniques. In this paper, the kernel PCA is proposed, which is able to remove outliers in data vectors and achieve dimension reduction. After de-noising, a new image segmentation approach based on pulse coupled neural network (PCNN) is presented. PCNN dynamically evaluates similarity between any two samples owing to the outstanding centralization characteristic based on the vicinity in space and the comparability of brightness. It has higher accuracy and faster performance than those classical clustering algorithms. The pulse coupled neural network clustering algorithm with de-noising by kernel PCA enhances robustness of the original clustering algorithms to noise. Experimental results with artificial and real-world images have shown the effectiveness of the proposed algorithm
Starting Page	561
Ending Page	566
File Size	337579
Page Count	6
File Format	PDF
ISBN	1424404657
DOI	10.1109/ICMA.2006.257614
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Image segmentation Neural networks Noise reduction Kernel Principal component analysis Clustering algorithms Data mining Feature extraction Brightness denosing PCNN kernel PCA image segmentation
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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