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Proceedings Paper

Image segmentation based on local Fourier coefficients histogram
Author(s): Feng Zhou; Jufu Feng; Qing-Yun Shi
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Paper Abstract

Image segmentation is a typical problem of image analysis. The aim is to partitioning a grayscale image to disjoint regions of coherent illuminance or homogenous texture. There are many segmentation methods of region-based, contour-based or region-contour-joint approaches to deal with different type images. Here we treat color coherent region as a special texture, and we used a new texture descriptor based on local Fourier coefficients histogram adaptive for this extended texture representation. Then a texture-based image segmentation algorithm is proposed. By utilizing the texture features of a region and the K-mean cluster algorithm we obtain a coarse segmentation of an image. Then by refining the region boundary iteratively a final segmentation can be resulted. Because our texture feature is also suitable for gray-coherence region, this algorithm can protect the gray-coherence from over-segmentation. For the same time, we reprove the boundary refinement by replaced with three steps: horizontal refinement, vertical refinement and boundary integrality checking. We also proposed the pre-processing and post-processing method for this algorithm. The segmentation performance is demonstrated on several synthesis texture images and aerial images.

Paper Details

Date Published: 21 September 2001
PDF: 6 pages
Proc. SPIE 4550, Image Extraction, Segmentation, and Recognition, (21 September 2001); doi: 10.1117/12.441496
Show Author Affiliations
Feng Zhou, Peking Univ. (China)
Jufu Feng, Peking Univ. (China)
Qing-Yun Shi, Peking Univ. (China)

Published in SPIE Proceedings Vol. 4550:
Image Extraction, Segmentation, and Recognition

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