In this paper, we present a unified framework for the analysis of video databases by using Markov spatio-temporal random walks on graph. The framework provides an efficient approach for both clustering, data organization, dimension reduction and recognition. The aim is to develop a visionbased approach for human behaviour recognition. Our contribution lies in three aspects. First, we employ 3D ...

Digital Watermarking allows an individual to add some hidden copyright notices or other verification messages to digital media, where message is a group of bits describing the information pertaining to the signal or its author. For this purpose, two techniques viz. global watermarking and local watermarking can be used. In this paper, the performance of two feature based global and local waterm...

In the paper, an effective method for reducing Geometrical Error (G.E) and Numerical Error (N.E) of Zernike moments is proposed. By running MATLAB for the proposed Zernike’s algorithm, the results of our proposed methods have shown a remarkable improvement to the total error of the analysis. The new proposed technique in reducing significantly Geometrical Error is performed better than that in ...

In this paper, we present a data hiding detection (steganalysis) method based on Zernike moments of discrete wavelet coefficients of an image and SVM. We use Zernike moments of DWT subbands coefficients of an images as features for steganalysis and use support vector machines (SVM) for classification of stego and non-stego images. Experimental results show that there are different between these...

This paper proposes a palmprint based verification system using low-order Zernike moments of palmprint sub-images. The Zernike moments of corresponding sub-images of live and enrolled palmprint are matched using Euclidean distance for verification. An efficient weighted fusion technique to fuse matching scores of the sub-images is proposed. The palmprint is extracted from the hand image acquire...

We extend the linear Radon transform to a nonlinear space and propose a method by applying the nonlinear Radon transform to Zernike moments to extract shape descriptors. These descriptors are obtained by computing Zernike moment on the radial and angular coordinates of the pattern image's nonlinear Radon matrix. Theoretical and experimental results validate the effectiveness and the robustness ...

In this paper, a Zernike moments-based descriptor is used as a measure of shape information for the detection of buildings from Very High Spatial Resolution (VHSR) satellite images. The proposed approach comprises three steps. First, the image is segmented into homogeneous objects based on the spectral and spatial information. MeanShift segmentation method is used for this end. Second, a Zernik...