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Multi-Resolution Color Image Segmentation Based on Fuzzy Clustering

Author: WangLiLi
Tutor: XiaoDeGui
School: Hunan University
Course: Computer Applications
Keywords: Color image segmentation Fuzzy Clustering Wavelet Transform Multi-resolution Mean Shift Nuclear methods
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 309
Quote: 2
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Abstract


Image segmentation is the basis of the image analysis, recognition and understanding from the image processing to the image analysis , a critical step . Color images provide richer information than the gray-scale image , the color image segmentation in recent years more and more people pay attention to one of the hot spots of the image technology research . This paper analyzes the current image segmentation algorithm based on fuzzy clustering is proposed a new color image segmentation method based on wavelet transform and fuzzy clustering . The main work and contributions are as follows : 1 multi-resolution characteristics of wavelet transform is applied to image segmentation , the minimum resolution of fuzzy clustering algorithm , the segmentation results under the current resolution is passed to the next resolution in order to achieve image segmentation, to achieve the purpose of to reduce segmentation algorithm calculated the amount of coarse to fine . 2 , the mean shift and cluster validity based on fuzzy C -means clustering (FCM) algorithm . First fast convergence of the mean shift initial segmentation algorithm on the conduct of the image , then use the segmentation results FCM algorithm to determine the initial cluster centers and the the combined cluster validity function to determine the optimal number of clusters . Experimental results show that the method combined with wavelet transform generated image segmentation algorithm , the conduct of the natural color image segmentation speed and effect are better than traditional FCM algorithm . 3 . Proposed a nuclear density function clustering and initialization for the fuzzy kernel clustering algorithm . Then combined to achieve a new fast color image segmentation algorithm and fuzzy kernel clustering and wavelet transform . After experimental simulation , the segmentation algorithm is fast and effective , and is better than the traditional FCM algorithm . This method , compared with the first method , the calculation time is increased slightly , but to get rid of the parameter settings of the impact, and to improve the quality of the segmentation .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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