The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The present article focuses on the classification of fingerprints. Our aim goal is to unify the process of fingerprint compression, classification and identification. The well known methods suited to these tasks are based on WSQ (Wavelet Scalar Quantization) for compression, Gabor filters for classification and minutiae matching for identification. We propose to use Block Ridgelet Transform (BRT)...
Face recognition has been a main object of study, producing robust systems with high reliability. However, these systems face the inconvenience of long processing times which are, in many cases, unwanted. This paper presents a simple face recognition approach from TV video files based on the redundancy of information and a face recognition system used in regular face pictures. More precisely, the...
The algorithm based on multi-feature and SVM is proposed. The paper firstly uses wavelet de-noising for gait images. The text offers to use width descriptors as gait features and combines lower angle features. The kernel-based Fisher criterion and support vector machine is combined to classification and identification. The gait characteristic is extracted by KFDA, which can obtain the best projection...
A new classification method called affine subspace nearest points (ASNP) algorithm is presented in this paper. Similar to the idea of the geometrical explanation of support vector machines (SVMs), the ASNP algorithm designed by us as a binary classifier extends the areas searched for the nearest points from the convex hulls in SVM to affine subspaces, and constructs the decision hyperplane separating...
The appearance of a surface texture is strongly dependent on the illumination direction. This is why current state-of-art surface texture classification methods require multiple training images captured under a variety of illumination conditions for each class. This paper presents an inexpensive method for illumination-invariant texture classification based on self-similarity and wavelet transform...
In this paper, we present a face recognition method based on the combination of the LoG-Gabor wavelets (GW) and the phase congruency (PC) method. The phase congruency feature images were obtained by applying phase congruency model to these multi-view face images with log-Gabor wavelets filters over 5 scales and 8 orientations, and then the mean and standard deviation of the image output are computed...
This paper presents the use of a template based method in order to make a head pose estimation. As an image classification problem the aim of this kind of techniques is to convert the input head image into a feature vector. The feature vectors of different persons taken at the same pose will serve to learn a head pose classifier. The aim of this work is to estimate the head pose of people looking...
In this paper, we introduce a face recognition approach based on the contourlet transform and support vector machine, which takes technological advantages of both support vector machine and the contourlet transform for feature extraction. The contributions of this paper include the following aspects: (1) support vector machine is successfully applied to face recognition by using the contourlet transform...
In this paper, we introduced a features fusion method for face recognition based on Fisher's Linear Discriminant (FLD). The method extract features by employed Two-Dimensional principal component analysis (2DPCA) and Gabor wavelets, and then fuse their features which are extracted with FLD respectively. As a holistic feature extraction method, 2DPCA performs dimensional reduction to the input dataset...
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...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.