This paper introduces a new approach to content based image retrieval by texture. There are three problems to solve: high computational time, handling high dimension data, and comparing images consistent with human perception. To decrease the computational, time, we present a new strategy to extract an image feature with high retrieval accuracy. We also propose how to reduce the image feature dimension using the reward-punishment algorithm, so any robust indexing methods can be used. By weighting the extracted image features, a system may perceive the image consistently with human perception.
Fast content-based image retrieval using quasi-Gabor filter and reduction of image feature dimension
2002-01-01
861021 byte
Conference paper
Electronic Resource
English
Fast Content-Based Image Retrieval Using Quasi-Gabor Filter and Reduction of Image Feature Dimension
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