NDLI: Color image segmentation based on wavelet transformation and S OFM neural network

Content Provider	IEEE Xplore Digital Library
Author	Jun Zhang Qieshi Zhang
Copyright Year	2007
Description	Author affiliation: Grad. Sch. of Inf., Production & Syst., Waseda Univ., Kitakyushu (Jun Zhang; Qieshi Zhang)
Abstract	Image segmentation, which is the first essential and fundamental issue in the image analysis and pattern recognition, is a classical difficult problem in the image processing. The color images, which possess more visual information than the gray images do, have aroused more and more attentions. In the medical imaging system, according to the different absorbency of different tissues, the staining method is often used to get the color image which provides more abundant information for diagnosis. As for the automatic analysis system of kidney-tissue image stained by Periodic Acid Schiff (PAS), the correct segmentation of glomerulus is an important step. A layer- color clustering segmentation method based on wavelet transformation and self-organizing feature map neural network (SOFM) is proposed in this paper. Firstly, the wavelet transformation is applied to the original images to get the low frequency images to improve the running efficiency. Secondly, the disordered method based on random number is performed to improve the performance of SOFM. Thirdly, the layer-color clustering using SOFM is executed until the final error can meet the need of the average color error (ACE) and then the clustered image and the palette can be acquired. Finally, based on the histogram of palette, the glomerulus can be segmented from the kidney-tissue image correctly. Experimental results show the good performance of this method.
Starting Page	1778
Ending Page	1781
File Size	461647
Page Count	4
File Format	PDF
ISBN	9781424417612
DOI	10.1109/ROBIO.2007.4522435
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Color Image segmentation Neural networks Frequency Biomedical imaging Medical diagnostic imaging Histograms Clustering algorithms Principal component analysis Robots layer-color clustering Wavelet transformation average color error SOFM neural network
Content Type	Text
Resource Type	Article

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