New Curvelet Features for Image Indexing and Retrieval

Abstract

Image descriptors encode the images in the database as feature vectors. Feature vectors play main role in content based image retrieval. This paper proposes a new feature vector based on wavelets. Most of the natural images have short span high frequencies and low frequencies extending for larger span. Hence, the design of our feature vector is such that it provides higher spatial localization and lower frequency resolution at higher frequencies and the reverse for lower frequencies. The energy of the frequency content of the image at various sub-bands and different spatial resolution (higher for higher frequency bands) is stored as feature vector. Thus, the given feature vector encodes high frequency information as well. The superiority of the proposed algorithm over some traditional algorithms is substantiated with results.