ICIP 2006, Atlanta, GA

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Paper Detail

Session:Visual Object/Event Detection, Segmentation, and Classification
Time:Wednesday, October 11, 14:20 - 17:00
Presentation: Poster
Topic: Image & Video Segmentation: Texture segmentation
Authors: Arshad Hussain; GIK Institute of Engineering Sciences & Technology 
 Nasir Rajpoot; University of Warwick 
 Kashif Rajpoot; GIK Institute of Engineering Sciences & Technology 
Abstract: In this paper, we present a novel texture classification algorithm inspired by the self-assembling behavior of real ants when building live structures with their bodies. The proposed algorithm employs dyadic Gabor filter banks for extracting discriminant features from images containing multiple textures not known to the algorithm. The feature space is clustered using the novel ant tree clustering (ATC) algorithm based on the similarity of ants carrying the feature vectors. The results thus obtained show promise of the proposed approach.