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Recently many works focus on the vehicle type recognition because it is important in security and authentication systems. Computational complexity and low recognition rate especially when the system has to recognize among a large number of vehicles, are two major problems in vehicle type recognition. In recent years wavelet and contourlet transform have been applied in the recognition tasks successfully...
This paper presents an identification-verification biometric system based on the combination of geometrical and palm-print hand features. It attempts to improve the performance of existing hand-geometry or palm-print systems which no combine both methods. 1440 hand images of 144 people with 10 samples each one have been acquired by a commercial scanner with 150 dpi resolution. 80 widths of fingers...
Method of image recognition based on statistics can achieve fine performance only if large numbers of samples are provided. In some situation, it's impossible to obtain so many samples, which may result in the poor recognition-performance because lacking of information. Furthermore, frequently-used neural network is designed as classifier with the purpose of empirical risk minimization and with poor...
This paper describes a road obstacle classification system that recognizes both vehicles and pedestrians in far-infrared images. Different local and global features based on Speeded Up Robust Features (SURF) were investigated and then selected in order to extract a discriminative signature from the infrared spectrum. First, local features representing the local appearance of an obstacle, are extracted...
Target recognition is a key step in the application of SAR images, but because of the existing of speckles in SAR images, targets can not be recognized well by using traditional methods. According to the advantages of invariant moments extraction and support vector machine (SVM) classification, an efficient method of SAR image target recognition is proposed. First, image preprocessing is performed...
In this paper, we propose a novel method for ear recognition using the contourlet transform. As first, we decompose the image using the contourlet transform. Then the features of the lowpass subband and the bandpass directional subbands are extracted respectively. Here we use the normalized gray-level co-occurrence matrix and the generalized Gaussian density to extract ear features. Finally, the two...
Breast cancer is the most common cancer among women. To assist the ultrasound (US) diagnosis of solid breast tumors, the lobulated contour feature quantified by boundary-based corner counts is studied to classify breast tumors as malignant or benign. The corner points in this research was detected based on wavelet transform (WT), and the classification selected through comparison is support vector...
Human body is a natural emitter of infrared ray. Usually the body temperature is different from that of surrounding. This leads to gray-scale difference between human body and background in infrared thermal image. So the method of infrared thermal imaging was presented to classify gaits. Firstly, infrared videos of 23 subjects were collected by using infrared thermal camera. Body silhouettes were...
An automatic target recognition (ATR) system based on rough set-support vector machine (RS-SVM) for SAR targets is proposed in this paper. The system combines the strong feature selection ability of rough set (RS) with the excellent classification ability of SVM together. The wavelet invariant moments firstly are extracted, then selected by using forward greedy numeral attribute reduction algorithm...
In order to improve the recognition rate of a sucker rod's defect and reduce the rapture possibility of the rod, the mixed characters include of wavelet packet energy character and the peak value in the time-domain were used as the input of a recognition network, and artificial neural networks (ANN) and support vector machines (SVM) were used and compared as the recognition network to get the best...
Human face recognition plays an important role in applications such as video surveillance, human computer interface, and face image database management. This paper presents an improved face recognition method for multi-pose face recognition in color images, which addresses the problems of illumination and pose variation. At first, color multi-pose faces image features were extracted based on Gabor...
This paper proposes a novel idea based feature selection in the verification system of palmprint, which can realize the specific feature selection for different user using genetic algorithm (GA). In the stage of enrollment, discrete wavelet transforms (DWT) and statistical methods are first used for feature extraction. Then GA is employed for feature selection, which means that each user has a specific...
In this paper we present a framework for detecting, recognizing, and localizing objects in overlapping multi-camera network. The three main components of the framework include background change detection, object recognition, and object localization. The background change detection is based on analyzing wavelet transform coefficients of small patches of non-overlapping 3D texture maps. Detected changed...
This paper proposed a new method of extracting texture features based on Gabor wavelet in different color space. In addition, the application of these features for bark classification applying radial basis probabilistic network (RBPNN) and SVM (support vector machine) has been used. To extract the bark texture features, Gabor filter the image has been filtered with four orientations and six scales...
De-noising the MRS data is a key processing in analysis of spectroscopy MRS data. This paper presents an effective method based on wavelet-transform and pattern recognition technologies. Upon the characteristics of MRS data, a new wavelet basis function was designed, and a de-noising method of free induction decay (FID) data using wavelet threshold to obtain better MRS spectrums was conduced; hence,...
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