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Texture Boundary Detection Using 2-D Gabor Elementary Functions

Bertin Rodolphe OKOMBI-DIBA, Juichi MIYAMICHI, Kenji SHOJI

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Summary :

A framework is proposed for segmenting image textures by using Gabor filters to detect boundaries between adjacent textured regions. By performing a multi-channel filtering of the input image with a small set of adaptively selected Gabor filters, tuned to underlying textures, feature images are obtained. To reduce the variance of the filter output for better texture boundary detection, a Gaussian post-filter is applied to the Gabor filter response over each channel. Significant local variations in each channel response are detected using a gradient operator, and combined through channel grouping to produce the texture gradient. A subsequent post-processing produces expected texture boundaries. The effectiveness of the proposed technique is demonstrated through experiments on synthetic and natural textures.

Publication
IEICE TRANSACTIONS on Information Vol.E84-D No.6 pp.727-740
Publication Date
2001/06/01
Publicized
Online ISSN
DOI
Type of Manuscript
PAPER
Category
Image Processing, Image Pattern Recognition

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