This paper validates a recognition system using bidimensional wavelet transforms as feature extractor and investigates the relevance of each subband image in the recognition process. An experiment to verify the efficiency of the wavelets was performed omitting the feature extraction step. Results show that information about the relevant image features are evenly distributed in all subband image...

Human has a duty to preserve the nature, preserving the plant is one of the examples. This research emphasis on ornamental plant that has functionality not only as ornament plant but also as a medicinal plant. Purpose of this research is to find the best of the particular feature extraction components from several wavelet transformations. It consists of Daubechies, Dyadic, and Dualtree complex ...

Mechanical anomaly is a major failure type of induction motor. It is of great value to detect the resulting fault feature automatically. In this paper, an ensemble super-wavelet transform (ESW) is proposed for investigating vibration features of motor bearing faults. The ESW is put forward based on the combination of tunable Q-factor wavelet transform (TQWT) and Hilbert transform such that faul...

This paper proposes a multiscale texture classifier which uses features extracted from both magnitude and phase responses of subbands at different resolutions of the dual-tree complex wavelet transform decomposition of a texture image. The mean and entropy in the transform domain are used to form a feature vector. The proposed method can achieve a high texture classification rate even for small...

In this paper, a new idea in machinery fault diagnostic by combining minimum-distance pattern-recognition and discrete wavelet transform (DWT) is presented. The method starts by forming the feature vector, which is basically the position vector of a point in the hyperspace spanned by the set of wavelet coefficients. These coefficients are obtained by expanding the measured signal from faulty ma...

A novel vowel feature extraction method via hybrid wavelet and linear prediction coding (LPC) is presented here. The proposed Arabic vowels recognition system is composed of very promising techniques; wavelet transform (WT) with linear prediction coding (LPC) for feature extraction and feed forward backpropagation neural network (FFBPNN) for classification. Trying to enhance the recognition pro...

In this paper, we study the human action recognition problem based on motion features directly extracted from video. In order to implement a fast human action recognition system, we select simple features that can be obtained from non-intensive computation. We propose to use the motion history image (MHI) as our fundamental representation of the motion. This is then further processed to give a ...

With an ever growing emphasis on security systems, automated personal identification based on biometrics has been getting extensive focus in both research and practical over the last decade. The methods for iris recognition mainly focus on feature representation and matching. As we known traditional iris recognition method is using Gabor Wavelet features, the iris recognition is performed by a ...

Two ̄ights of the UKMeteorological Oce's Hercules aircraft through daytime frontal cirrus around Scotland have been analysed using wavelet analysis on the vertical velocity time-series from the horizontal runs. It is shown that wavelet analysis is a useful tool for analysing the turbulence data in cirrus clouds. It ®nds the largest scales involved in producing turbulence, as does Fourier analy...

Iris recognition is emerging as one of the important methods of biometrics-based identification system. It consists of five major steps iris acquisition, segmentation, normalization, feature extraction and matching. In this work, we used Wavelet transform function in place of Hough transform function. After extraction of feature of iris used feature optimizations technique for better selection ...