A biologically-inspired computational model for perceiving the TROIs from texture images

Authors:
Woobeom Lee;Wookhyun Kim
Affiliations:
Department of Computer Engineering, Yeungnam University, Gyeongsan-si, Gyeongbuk-do, Republic of Korea;Department of Computer Engineering, Yeungnam University, Gyeongsan-si, Gyeongbuk-do, Republic of Korea
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

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Abstract

This paper presents a biologically-inspired method of perceiving the TROIs(: Texture Region Of Interest) from various texture images. Our approach is motivated by a computational model of neuron cells found in the primary visual cortex. An unsupervised learning schemes of SOM(: Self-Organizing Map) is used for the block-based image clustering, plus 2D spatial filters referring to the response properties of neuron cells is used for extracting the spatial features from an original image and segmenting any TROI from the clustered image. To evaluate the effectiveness of the proposed method, various texture images were built, and the quality of the extracted TROI was measured according to the discrepancies. Our experimental results demonstrated a very successful performance.