Currently, it is very essential to monitor activities in Video surveillance applications both in private and public environments. In this context, our paper presents a novel framework to detect the normal or abnormal event situations by analyzing the pixel-wise motion context using block-based approaches. First motion estimation techniques are applied to characterize the events at the pixel lev...

The proliferation of digital audio file is costing loss of revenue to the owner of copyright information especially in the music industry. The paper brings to view works done by various on digital audio watermarking and using discrete wavelet transform (DWT) and discrete cosine transform (DCT) with chaotic watermarking towards carrying out investigation for real life application.

Image compression is a method that is used to reduce the irrelevance and redundancy of the image data i.e reduce the storage space for images ,video in order to increase the performance of transmission process in an efficient form without compromising the quality and information of images. This paper deals with two image compression techniques. The first one is Discrete Cosine Transform (DCT) a...

Piracy is a big threat to the original contents. This multi-model approach interleaves some frequency domain watermarking strategies to counteract shortcomings of one strategy by the advantages of other. The original image is divided into spatially disjoint blocks. Watermarking is a way of embedding a mark that hides information in a multimedia carrier. Major issues in Image watermarking are to...

Abstract In this study, wavelet support vector machine (WSWM) model is proposed for daily suspended sediment (SS) prediction. The WSVM model is achieved by combination of two methods; discrete wavelet analysis and support vector machine (SVM). The developed model was compared with single SVM. Daily discharge (Q) and SS data from Yadkin River at Yadkin College, NC station in the USA were used. I...

This study presents a framework for gray texture classification based on wavelet and curvelet features. The two main frequency domain transformations Discrete Wavelet Transform (DWT) and Discrete Curvelet Transform (DCT) are analyzed. The features are extracted from the DWT and DCT decomposed image separately and their performances are evaluated independently. The performance metric used to ana...

Discrete non-redundant wavelet transforms have been successfully applied previously in image compression applications [2], [6], [17]. However, the lack of translation invariance and aliasing present after the decomposition stage [3] may introduce undesirable artifacts for the analysis of medical signals and images, and can justify the use of a redundant wavelet representation. The discrete dyad...

We give a brief review of some of the wavelet-based techniques currently available for the analysis of arbitrary-length discrete time series. We discuss the maximal overlap discrete wavelet packet transform (MODWPT), a non-decimated version of the usual discrete wavelet packet transform, and a special case, the maximal overlap discrete wavelet transform (MODWT). Using least-asymmetric or coifle...

this paper presents a new coding method for image compression based on jpeg2000 and contourlet transform. jpeg2000 standard is a common standard that uses discrete wavelet transform (dwt) in the compression process. the main problems of dwt are failure to detect curved edges in image and its shortage representation of the ridge and furrow patterns which cause deficiency and block artifacts rema...