24 results for “Wavelet feature extraction”

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Research ArticleOpen accessIn the abstractImage Recognition Using Combination of Discrete Multi_Wavelet and Wavenet TransformDr Mikhled AlfaouriFocus of the method was to present image identification and labeling using new combination of dynamic transforms. This method is based on using the combination of the Discrete Multi-wavelet Transform (DMWT) and Wavenet Transform (WN). In this method, the resulting coefficients were computed by the proposed multi-wavelets transform for single-level decomposition. The low pass sub bands of the upper left … …American Journal of Applied Sciences, Vol. 5, Issue 4 · 30 Apr 2008 · 7,088 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordDetection and Diagnostic Approach of COVID-19 Based on Cough Sound AnalysisMuzhir Shaban Al-Ani, Thabit Sultan Mohammed, Awni Ismail Sultan et al.Coronavirus (COVID-19) started at the end of 2019 and then spread out around the world as a pandemic at the beginning of 2020. At that time, researchers began to work on detecting and diagnosing this virus, where many methods have been applied for this reason. This study focuses on how to diagnose coronavirus through patients’ cough. Accordingly, real samples were … …Journal of Computer Science, Vol. 17, Issue 6 · 29 Jun 2021 · 7,803 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordA GAUSSIAN MIXTURE MODEL FOR CLASSIFYING THE HUMAN AGE USING DWT AND SAMMON MAPJ. Nithyashri, G. KulanthaivelThe appearance of a human face rigorously changes with respect to age that makes Age Classification as a more challenging task. The algorithms such as, K-Nearest Neighbor (K-NN), Support Vector Machine (SVM), Radial Basis Function (RBF), motivated many Face Researchers to focus their attention in classifying the human age into various age groups. The Classification rate produced by these existing … …Journal of Computer Science, Vol. 10, Issue 11 · 20 Dec 2014 · 7,707 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordPrincipal Component Analysis Based Feature Extraction, Morphological Edge Detection and Localization for Fast Iris RecognitionM. Suganthy, P. RamamoorthyThis study involves the Iris Localization based on morphological or set theory which is well in shape detection. Principal Component Analysis (PCA) is used for preprocessing, in which the removal of redundant and unwanted data is done. Applications such as Median Filtering and Adaptive thresholding are used for handling the variations in lighting and noise. Features are extracted using Wavelet … …Journal of Computer Science, Vol. 8, Issue 9 · 9 Aug 2012 · 7,748 accessesView PDF Cite