Content-Based Image Retrieval Using Wavelet Packets and Fuzzy Spatial Relations

Abstract

Abstract. This paper proposes a region based approach for image retrieval. We develop an algorithm to segment an image into fuzzy regions based on coefficients of multiscale wavelet packet transform. The wavelet based features are clustered using fuzzy C-means algorithm. The final cluster centroids which are the representative points, signify the color and texture properties of the preassigned number of classes. Fuzzy Topological relationships are computed from the final fuzzy partition matrix. The color and texture properties as indicated by centroids and spatial relations between the segmented regions are used together to provide overall characterization of an image. The closeness between two images are estimated from these properties. The performance of the system is demonstrated using different set of examples from general purpose image database to prove that, our algorithm can be used to generate meaningful descriptions about the contents of the images.

Clickjacking Attack: Hijacking User’s Click

“…In CBIR system the relevant database images with respect to the user's defined image are recovered using the features like texture, color, and shape [162]. But there was a need for more sophisticated image retrieval system for this a method based on the wavelet packets was introduced.…”