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Edge feature extraction of X-ray images plays an important role in detecting the fractures in bones. It deals with the detection of discontinuities in the gray level values which helps the medical practisioners to extract the edges of an images to detect the minute fractures of an X-ray bone image. Edge feature extraction of X-ray images using Multiresolution Analyis (MRA) based on biorthogonal wavelet...
Fetal Electrocardiogram (FECG) signal, non-invasively taken from the Abdominal Electrocardiogram (AECG) of a pregnant woman is a efficient diagnostic tool for determining congenital cardiac defects. Clinically significant information in the Fetal Electrocardiogram signal is often masked by Maternal Electrocardiogram (MECG) considered as the most predominant interference, power line interference, and...
Image segmentation is a computationally expensive and complex task that continuously focuses on performance challenges due to tremendous increase in the volume of high resolution images. Nowadays, shared memory multicore parallel programming architectures using OpenMP is emerging as an attractive computing platform for both general purpose and scientific computations due to their immense processing...
In the satellite images the noise is present such as mist, clouds etc., to remove the noise the Haar wavelet transforms are applied. Using the Image segmentation algorithm the major issue Deforestation is evaluated by comparing the image taken from the year 1939 and 2000. Deforestation is a serious issue that most nations face today. Deforestation is primarily due to the urbanization. Most nations...
In this paper, voice signal compression (VSC) is a technique that is used to convert the voice signal into encoded form and when compression is required, it can be decoded at the closest approximation value of the original signal. This work present a new algorithm to compress voice signals by using an ldquoadaptive wavelet packet decomposition and psychoacoustic modelrdquo. The main goals of this...
In this paper, voice signal compression and spectrum analysis (VSCSA) is a technique that is used to compress transparent high quality voice signals upto 45% - 60% of the source file at low bit rate 45 kbps with same extension (i.e. .wav to .wav), then voice spectrum analysis (VSA) is started. Voice signal compression (VSC) is done by using adaptive wavelet packet a tool of MatLab for decomposition...
In this paper we propose a steganography technique based on Stantlet transform and T-codes. The Stantlet transform are wavelet-like transforms that provides better time localization and signal compression than the conventional discrete cosine transforms (DCT) and discrete Haar-wavelet transforms. T-codes are used for better embedding capacity and decoding efficiency. The proposed method first encodes...
In this paper we address the issue of enhancement in the quality of scanned images of old manuscripts. Small portions of the text in these manuscripts have degraded with time and are not readable. We propose a segmentation based histogram matching scheme for enhancing these degraded text regions. To automatically identify the degraded text we use a matched wavelet based text extraction algorithm followed...
This paper presents an algorithm for recognition and segmentation of natural features in unstructured environments. By providing a Bayesian solution for the density estimation problem, the algorithm needs significantly less training data than conventional techniques and is applicable to different environments. The algorithm is based on colour and wavelet convolution of image patches to model the information...
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