An adaptive clustering and chrominance-based merging approach for image segmentation and abstraction

We present a novel, computationally efficient approach for natural image segmentation that uses the adaptive clustering algorithm (ACA) to obtain an initial segmentation and chrominance-based region merging to consolidate regions of perceptually uniform texture. The combination of ACA and chrominanc...

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Bibliographic Details
Published in:2010 IEEE International Conference on Image Processing pp. 241 - 244
Main Authors: He, Lulu, Pappas, Thrasyvoulos N.
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2010
Subjects:
Adaptive clustering algorithm
bilateral filtering
Clustering algorithms
Image color analysis
Image edge detection
Image segmentation
Merging
Pixel
region merging
Smoothing methods
ISBN:9781424479924, 1424479924
ISSN:1522-4880
Online Access:Get full text
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Summary:We present a novel, computationally efficient approach for natural image segmentation that uses the adaptive clustering algorithm (ACA) to obtain an initial segmentation and chrominance-based region merging to consolidate regions of perceptually uniform texture. The combination of ACA and chrominance-based merging preserves salient edges and smooths out noise and edges within textured regions. It can thus be used for image abstraction. Experimental results with natural images indicate the effectiveness of the proposed approach.
ISBN:9781424479924
1424479924
ISSN:1522-4880
DOI:10.1109/ICIP.2010.5651905