Showing papers by "Malay K. Kundu published in 2009"
TL;DR: This paper presents a new image retrieval scheme using visually significant point features extracted using a fuzzy set theoretic approach, which shows the robustness of the system is also shown when the images undergo different transformations.
69 citations
TL;DR: Fast Walsh transform (FWT) based SS image watermarking scheme is proposed that serves the dual purposes of authentication in data transmission as well as QoS assessment for digital media through dynamic estimation of the wireless channel condition.
47 citations
04 Feb 2009
TL;DR: The MxM sub-bands are used as primitive features, over which energies computed in a neighborhood are taken as the features for each pixel of the image.
Abstract: Feature Extraction algorithm is a very important component of any retrieval scheme. We propose M-band Wavelet Transform based feature extraction algorithm in this paper. The MxM sub-bands are used as primitive features, over which energies computed in a neighborhood are taken as the features for each pixel of the image. These features are clustered using FCM to obtain image signature for similarity matching using the Earth Mover's Distance. The results obtained were compared with MPEG-7 content descriptor based system and found to be superior.
8 citations
07 Jun 2009
TL;DR: A simple relevance feedback mechanism is proposed, that learns user's interest and updates feature weights based on a fuzzy feature evaluation measure, that has an advantage of handling comparatively small number of samples over those using standard classifiers involving large number of training samples and having more complexity.
Abstract: In this paper, an interactive image retrieval scheme using MPEG-7 visual descriptors is proposed. The performance of image retrieval systems is still limited due to semantic gap, which is created from the discrepancies between the computed low-level features (color, texture, shape, etc.) and user's conception of an image. As a result, more interest has been created towards development of efficient learning mechanism other than designing sophisticated low-level feature extraction algorithms. A simple relevance feedback mechanism is proposed, that learns user's interest and updates feature weights based on a fuzzy feature evaluation measure. This has an advantage of handling comparatively small number of samples over those using standard classifiers involving large number of training samples and having more complexity. Extensive experiments have been performed to test to what extent the performance of an image retrieval system can be enhanced further using MPEG-7 standard visual features at minimum cost.
4 citations