The recently developed theory of wavelets has a remarkable property to \zoom in" on very short lived frequency phenomena, such as transients in signals and singularities in functions, and hence provides an ideal tool to study localized changes. This paper proposes a wavelet method to estimate jump and sharp cusp curves of a function in the plane. The method is rst to compute wavelet transformat...

In dynamic targets tracking measure system, a new detection algorithm on infrared small target is put forward. The algorithm is base on wavelet transformation, and by using it we can gain clear characteristics of target image and decrease mistake of tracking target. In paper, the principle of infrared small target detection was introduced, and the infrared small target detection system is desig...

ÐDyadic wavelet transform has been used to derive an affine invariant function. First, an invariant function using two dyadic levels is derived. Then, this invariant function is used to derive another invariant function using six dyadic levels. We introduced the wavelet-based conic equation. The invariant function is based on analyzing the object boundary using the dyadic wavelet transform. Exp...

Wavelet mathematical transformation and heart sound signal processing have recently been attracting a significant amount of attention in the research community. Why is this new priority being given to improved approach to heart sound signal analysis for accurate pattern recognition using the wavelet transform technique? This article provides an overview of this emerging field of digital bio-sig...

Recognizing objects that have undergone certain viewing transformations is an important problem in the field of computer vision. Most current research has focused almost exclusively on single aspects of the problem, concentrating on a few geometric transformations and distortions. Probably, the most important one is the affine transformation which may be considered as an approximation to perspe...

The large numbers of images has posed increasing challenges to computer systems to store and manage data effectively and efficiently. This paper implements a CBIR system using different feature of images through four different methods, two were based on analysis of color feature and other two were based on analysis of combined color and texture feature using wavelet coefficients of an image. To...

The Discrete Wavelet Transform is the most powerful and new signal compression technique which uses multiresolution analysis for analyzing speech signal. Here we are doing parallel speech compression using two different wavelet transforms like Haar wavelets and Bi-orthogonal wavelet transformation (Bior). The resultant of components which are in high frequency bands are fusioned together and di...

In this study, hybrid Particle Swarm Optimization (PSO)-based Wavelet Neural Network (WNN) for natural scene text extraction is presented. In our approach, wavelet transformation is done on the different current and the wavelet coefficients are obtained. The wavelet coefficients are given as inputs to the wavelet neural network trained by Particle Swarm Optimization (PSO-WNN). The final network...