lung Cancer is believed to be among the primary factors for death across the world. Within this paper, statistical and machine learning techniques are employed to build a computer aided diagnosis system for the purpose of classifying lung cancer. The system includes preprocessing phase, feature extraction phase, feature selection phase and classification phase. For feature extraction, wavelet t...

In this paper, we present the application of the Type II Local Discriminant Basis (LDB) technique to feature extraction for land use classification in Synthetic Aperture Radar (SAR) images. Our classification algorithm incorporates spatial information into the decision process by classifying small image blocks, instead of single pixels. A feature vector composed of all the values in the image b...

Texture can describe a wide variety of surface characteristics and a key component for human visual perception and plays an important role in image-related applications. This paper proposes a scheme for texture image classification using visual perceptual texture features and Gabor wavelet features. Three new texture features which are proved to be in accordance with human visual perceptions ar...

In this work, event related potentials (ERPs) induced by visual stimuli categorized with different value of affective valence are studied. EEG signals are recorded during visualization of selected pictures belonging to International Affective Picture System (IAPS). A Morlet wavelet filter is used to transform the EEG input space to a topography-time–frequency feature space. Support vector machi...

Two kinds of wavelet features are proposed: (a) Kirsch edge enhancement based 2D wavelets and (b) 2D complex wavelets. The two sets of hybrid features are congregated by combining them with the geometrical features for the recognition of handwritten numerals. Experiments conducted on handwritten numeral recognition and verification show that the two hybrid feature sets can achieve high recognit...

This paper investigates the importance of spectrotemporal characteristics of the source excitation signal for speaker recognition. We propose an effective feature extraction technique for obtaining essential timefrequency information from the linear prediction (LP) residual signal, which are closely related to the glottal excitation of individual speaker. With pitch synchronous analysis, wavele...

In Electroencephalography (EEG) processing one of the crucial step is to select the features which can be used to characterize the different patterns. This paper presents relative wavelet energy as a new feature extraction technique to recognize the sleep EEG patterns. Experimental results on the Physionet databases with different sleep stages indicate that the relative wavelet energy is a comp...

Texture analysis is an important characteristic for automatic visual inspection for surface and object identification from medical images and other type of images. This paper presents an application of wavelet extension and Gray level cooccurrence matrix (GLCM) for diagnosis of myocardial infarction tissue from echocardiography images. Many of applications approach have provided good result in ...

One of the most common heart disease is congestive heart failure. In this study, the detail coefficients of RR interval data obtained from the discrete wavelet transform are applied for congestive heart failure (CHF) classification. The wavelet-based feature examined is a difference between the logarithms of variances of detail coefficients of RR interval data corresponding to two consecutive l...