Image Classification Based on Hierarchical Temporal Memory and Color Features
Radoslav Škoviera, Ivan Bajla · 2013
The research in the domain of content-based image retrieval (CBIR) is concentrated on several problems, among which two problems are essential: - development of efficient image classification algorithms, and selection of suitable image features. Recently, a biologically inspired Hierarchical Temporal Memory (HTM) network demonstrated promising results in image classification tasks. The focus of this paper is to explore possibilities of this network to be applied to CBIR. In particular, we study the performance of the HTM network when, instead of conventional grey-level images and features, color features are used. The results of our experiments show that using color texture features, defined for a reduced range of color quantization values, performs comparably well as the grey-scale image features.