Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Computing perceptual organization in computer vision
Computing perceptual organization in computer vision
Combining the evidence of multiple query representations for information retrieval
TREC-2 Proceedings of the second conference on Text retrieval conference
Matching performance of binary correlation matrix memories
Transactions of the Society for Computer Simulation International - Special issue: simulation methodology in transportation systems
Information Retrieval
A Retrieval Mechanism for Semi-Structured Photographic Collections
DEXA '97 Proceedings of the 8th International Conference on Database and Expert Systems Applications
Retrieval of trademark images by means of size functions
Graphical Models - Special issue on the vision, video and graphics conference 2005
Gestalt-based feature similarity measure in trademark database
Pattern Recognition
Practice and challenges in trademark image retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
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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.