Texture Boundary Detection Using 2-D Gabor Elementary Functions

Bertin Rodolphe OKOMBI-DIBA  Juichi MIYAMICHI  Kenji SHOJI  

IEICE TRANSACTIONS on Information and Systems   Vol.E84-D    No.6    pp.727-740
Publication Date: 2001/06/01
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Processing, Image Pattern Recognition
Gabor filters,  feature extraction,  edge detection,  channel grouping,  texture segmentation,  

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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.