MULTI-FEATURE CONTENT-BASED IMAGE RETRIEVAL

Abstract

In this paper, we propose a model for the fast retrieval image data using multiple features based on multiresolution processing. We demonstrate our performance results by searching an image database of approximately 30,000 24-bit color photographic images. We use identical structures to build the index keys from the two features using histogram generation and wavelet transform. The experiments show that the results obtained with the quad-tree structure for the two features are more accurate than using just one feature; however, the retrieval time almost doubles. The retrieval time can be improved by applying our weighted cascading comparison scheme, which allows the weighting of the features to control a pipeline. We evaluate our multiplefeature similarity-matching algorithm by comparing its accuracy with a regular-matching algorithm. The results also show that the retrieval time of our weighted cascading scheme is faster than the regular matching algorithm with an acceptable accuracy....