Trademark Image Retrieval Using Multiple Features

This paper describes an ongoing research project aimed at implementing a trademark retrieval system using an associative memory neural network. The novel aspect presented in this paper is the proposed integrated framework for image retrieval using multiple representations of images based on gestalt principles. In this paper we summarise the methods we followed in extracting local perceptual features as well as features of the closed figures of images. In designing the search engine of the system we have adopted a novel similarity assessment criteria based on local features as well as features of the closed figures, which is being implemented using an associative memory neural network to achieve high performance in retrieval. Then we describe the strategy we followed in combining multiple similarity measures and present the results obtained from the first phase of evaluation of the system.