Showing papers by "Malay K. Kundu published in 2003"

Fingerprint minutiae matching using scoring techniques

Abstract: Disclosed is a method and apparatus to provide for fingerprint minutiae matching using scoring techniques. A plurality of minutiae in a fingerprint image is defined. A score associated with each minutia corresponding to the validity of each minutia is estimated. The fingerprint image is then matched against one or more sample fingerprint images utilizing a partial point set pattern matching (PSPM) algorithm.

Segmentation of remotely sensed images using wavelet features and their evaluation in soft computing framework

Abstract: The present paper describes a feature extraction method based on M-band wavelet packet frames for segmenting remotely sensed images. These wavelet features are then evaluated and selected using an efficient neurofuzzy algorithm. Both the feature extraction and neurofuzzy feature evaluation methods are unsupervised, and they do not require the knowledge of the number and distribution of classes corresponding to various land covers in remotely sensed images. The effectiveness of the methodology is demonstrated on two four-band Indian Remote Sensing 1A satellite (IRS-1A) images containing five to six overlapping classes and a three-band SPOT image containing seven overlapping classes.

Extraction of features using M-band wavelet packet frame and their neuro-fuzzy evaluation for multitexture segmentation

Abstract: In this paper, we propose a scheme for segmentation of multitexture images. The methodology involves extraction of texture features using an overcomplete wavelet decomposition scheme called discrete M-band wavelet packet frame (DMbWPF). This is followed by the selection of important features using a neuro-fuzzy algorithm under unsupervised learning. A computationally efficient search procedure is developed for finding the optimal basis based on some maximum criterion of textural measures derived from the statistical parameters for each of the subbands. The superior discriminating capability of the extracted features for segmentation of various texture images over those obtained by several existing methods is established.

M-band wavelets: application to texture segmentation for real life image analysis

Abstract: This paper describes two examples of real-life applications of texture segmentation using M-band wavelets. In the rst part of the paper, an ecien t and computationally fast method for segmenting text and graphics part of a document image based on textural cues is presented. It is logical to assume that the graphics part has dieren t textural properties than the non-graphics (text) part. So, this is basically a two-class texture segmentation problem. The second part of the paper describes a segmentation scheme for another real-life data such as remotely sensed image. Dieren t quasi-homogeneous regions in the image can be treated to have dieren t texture properties. Based on this assumption the multi-class texture segmentation scheme is applied for this purpose.

Content based image retrieval with fuzzy geometrical features

Abstract: This paper presents a robust technique for Content Based Image Retrieval (CBIR) using fuzzy edge map of an image. Fuzzy compactness vector is computed from fuzzy edge map thresholded at different levels of the unsegmented image, which also incorporates gray level contrast information embedded in the edges. The resemblance of two images is defined as the similarity between the computed feature vectors.

Robust digital image watermarking utilizing a Walsh transform algorithm

Abstract: Disclosed is a method, apparatus, and system to provide for robust digital image watermarking utilizing a Walsh transform algorithm. A first image processor performs operations including partitioning a cover image, generating a key, and inserting a watermark symbol into the cover image utilizing a Walsh transform and the key. A second image processor performs operations including extracting the watermark symbol from the cover image utilizing a Walsh transform and the key.

Robust and low cost watermarking using image characteristics

Abstract: Most of the digital image watermarking techniques use pixel values, frequency or other transform coefficients to embed information without considering the perceptually significant portion of the cover. The present work selects the perceptually significant region of the cover and embeds data in the transform coefficients in order to design low-cost robust watermarking scheme. Experimental results using several benchmark image samples are reported.

Digital watermarking using homogeneity in image

Abstract: A new technique of digital watermarking for gray-level images is reported in this paper. Digital watermarking/hiding has emerged as a new area of research in connection to intellectual property (IP) protection of images. The redundancy in image representation can be exploited successfully to hide some characteristic information in images, without noticeable distortion. Hidden information after extraction, can be used to protect copyright. This article deals with a block-based technique for inserting a copyright mark (invisible logo) into a gray-level image. The robustness of the proposed method has been tested against non-destructive attacks like mean and median filtering.