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In this paper, a novel feature extraction method based on the utilization of wavelet packet transform (WPT) and the concept of fuzzy entropy is presented. The method acts in steps, were in the first step the WPT is employed to generate a wavelet decomposition tree from which many features are extracted. In the second step, a new algorithm to compute the fuzzy entropy is developed and adopted as a...
This paper presents a novel audio classification algorithm, which combines the rule-based with model-based method in an efficient way. First, the threshold-based method is performed over each audio clip for preclassification, with three typical features utilized and majority rule applied. Next, a weighted frame-based Support Vector Machine (SVM) is presented for further classification, using a new...
The characteristics of human footsteps are determined by the gait, the footwear and the floor. Accurate footstep analysis would be useful in various applications, home security service, surveillance and understanding of human action since the gait expresses personality, age and gender. The feasibility of personal identification has been confirmed by using the feature parameter of footsteps, however,...
Many algorithms do not work well in real-world systems as real-world systems have problems with illumination variation and imperfect detection of face and eyes. In this paper, we compare the illumination normalization methods (SQI, HE, GIC), and the feature extraction methods (PCA, LDA, 2dPCA, 2dLDA, B2dLDA) using Yale B database and ETRJ database. In addition, we propose a stable and robust illumination...
In this paper an optimum wavelet for denoising and detection applications is designed. The approach is based on searching for a wavelet basis that provides the best non linear approximation of a given signal. It is shown that such a basis will have the best wavelet denoising performance in the sense of signal estimation error. In addition, such a wavelet can represent the signal more compactly with...
Since the 1990s, there have been various lane detection systems designed to suit various road conditions such as highways, urban and rural roads. Current research has shown to predominantly detect only 1 lane marking set in real time and is unable to provide additional lanes for support in situations such as lane closures, road work conditions and car accidents that may obstruct the driving lane....
Text classification has been considered as a hot research area in data mining. This paper presents a new approach combining hidden Markov model (HMM) with support vector machine (SVM) for text classification. HMMs are used to as a feature extractor and then a new feature vector is normalized as the input of SVMs, so the trained SVMs can classify unknown texts successfully. The experimental results...
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