Robust and Comprehensive Image Classification Systems Using Gabor Wavelets and Shape Features for Categorizing Color Image

In this paper a new and reliable method of improving retrieval performance, and which complement feature weighting is proposed. The system is comprehensive because it incorporates Wavelet filters of different grid sizes and flexible because the feature weights can be adjusted to achieve retrieval refinement according to user’s need and robust because the system’s algorithm is applicable to retrieval in all kinds of image database. In this paper, textural features derived from six grid sizes of independent and different Wavelet filter banks were incorporated into the CBIR system by taking advantage of the fact that each grid size of filter is suited to capture particular set of localized frequency-images in diverse database.