Title :
Texture Segmentation using Ant Tree Clustering
Author :
Channa, Arshad Hussain ; Rajpoot, Nasir Mahmood ; Rajpoot, Kashif Mahmood
Author_Institution :
Fac. of Comput. Sci. & Eng., GIK Inst.
Abstract :
Motivated by the self-assembling behavior of real ants, we present a novel algorithm for texture segmentation which is based on ant tree clustering of wavelet features. In a pattern recognition setting, wavelet features are extracted using either of the two subband filtering methods: discrete wavelet transform (DWT) or discrete wavelet packet transform (DWPT). The feature classification process is inspired by the self-assembling behavior observed in real ants where ants progressively become attached to an existing support and then successively to other attached ants thus building trees based on the similarity of feature vectors. The results thus obtained compare favorably to those of other recently published filtering based texture segmentation algorithms
Keywords :
artificial life; discrete wavelet transforms; feature extraction; image classification; image segmentation; image texture; pattern clustering; ant tree clustering; discrete wavelet packet transform; discrete wavelet transform; feature classification; pattern recognition; self-assembling behavior; texture segmentation; wavelet features extraction; Algorithm design and analysis; Clustering algorithms; Computer science; Discrete wavelet transforms; Feature extraction; Filtering; Image segmentation; Image texture analysis; Partitioning algorithms; Wavelet analysis; ant tree clustering; feature extraction; texture segmentation & analysis; wavelet transform;
Conference_Titel :
Engineering of Intelligent Systems, 2006 IEEE International Conference on
Conference_Location :
Islamabad
Print_ISBN :
1-4244-0456-8
DOI :
10.1109/ICEIS.2006.1703192