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Showing papers by "Malay K. Kundu published in 2006"


Proceedings ArticleDOI
01 Jan 2006
TL;DR: This paper proposes a new image retrieval scheme using visually significant features that combines illumination, viewpoint invariant color features, and relative importance of the features is evaluated using a fuzzy entropy based measure from relevant and irrelevant set of the retrieved images marked by the users.
Abstract: This paper proposes a new image retrieval scheme using visually significant features. Clusters of points around significant curvature regions (high, medium, weak type) are extracted to obtain a representative image. Illumination, viewpoint invariant color features are computed from those points for evaluating similarity between images. Relative importance of the features is evaluated using a fuzzy entropy based measure computed from relevant and irrelevant set of the retrieved images marked by the users. The performance of the system is tested using different set of examples from general purpose image database. Robustness of the system has also been shown when the images have undergone different transformations.

21 citations


Proceedings ArticleDOI
01 Jan 2006
TL;DR: The present investigation has shown that the decoding complexity of higher N-values can be overcome at moderate M-values while robustness performance is maintained at satisfactory level.
Abstract: Performance of a digital image watermarking algorithm, in general, is indicated by perceptual invisibility, data hiding capacity and robustness to some types of attacks. The work reported in this paper uses a novel channel coding, M-band wavelet decomposition and N-ary modulation principle for performance improvement in spread spectrum image watermarking. Watermark casting process may be divided in two steps: in first step a gray scale watermark image is represented by less number of binary digits using novel channel coding and spatial biphase modulation principle. In the second step, the intermediate binary watermark is embedded in selective M-band wavelets channels using N-ary modulation technique. Each watermark bit is embedded in the two different set of subbands having high and low variance values so that faithful decoding is possible against varieties of external attacks. The present investigation has shown that the decoding complexity of higher N-values can be overcome at moderate M-values while robustness performance is maintained at satisfactory level.

11 citations


Proceedings ArticleDOI
01 Jan 2006
TL;DR: A robust segmentation technique based on fuzzy set theory for brain MR images is proposed and the effectiveness of the proposed algorithm, along with a comparison with other methods, has been demonstrated on a set ofbrain MR images.
Abstract: Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of magnetic resonance (MR) images. A robust segmentation technique based on fuzzy set theory for brain MR images is proposed in this paper. The histogram of the given image is thresholded according to the similarity between gray levels. The similarity is assessed through second order fuzzy correlation. To calculate the second order fuzzy correlation, a modified co-occurrence matrix is used to extract the local information more accurately. Two parameters - ambiguity and the strength of ambiguity, are introduced to determine the thresholds of the given histogram. The effectiveness of the proposed algorithm, along with a comparison with other methods, has been demonstrated on a set of brain MR images.

9 citations


Book ChapterDOI
13 Dec 2006
TL;DR: In this paper, a region based approach for image retrieval is proposed, where the wavelet based features are clustered using fuzzy C-means algorithm and the final cluster centroids which are the representative points signify the color and texture properties of the preassigned number of classes.
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.

4 citations



Proceedings ArticleDOI
01 Jan 2006
TL;DR: Experimental result shows the effectiveness of the proposed watermarking scheme, which could be used as an inexpensive method of copyright protection for printed document like passport, id card etc.
Abstract: This paper describes a method of hiding a copyright symbol into an print image which can survive against print-scan process. Copyright protection is a challenging problem specially for printed image document. Digital watermarking is one of the most efficient method to protect an image from unauthorized use. In this paper we propose an inexpensive hardcopy watermarking technique which can survive print-scan transformation as well as small degree of geometric distortion. Experimental result shows the effectiveness of the proposed watermarking scheme. The proposed scheme could be used as an inexpensive method of copyright protection for printed document like passport, id card etc.

1 citations