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In order to solve the small sample problems and the linear inseparable problems caused by some nonlinear factors, this paper proposed a method to generate multiple virtual samples similar to the original images by its class, then all virtual samples were combined as a new database for training. The method not only helps to increase more samples, but strengthens the reliance of virtual samples on the...
Face recognition, one of the most explored themes in biometry, is used in a wide range of applications: access control, forensic detection, surveillance and monitoring system, robotic and human machine interaction. In this paper, a new classifier is proposed for face recognition. The performance of this new classifier is compared with the performance of the KNN classifier. The face image database...
This paper proposes a key motion spotting method which is designed to locate the motion of interest (or key motion) from a database of motion sequences. As a key motion could be just a subsequence of the stored motion sequence, the proposed method differs much from the general methods of content-based retrieval of motion sequences, which searches from the database the individual sequences similar...
Based on the recent success of Low-Rank matrix Representation (LRR), we propose a novel classification method for robust face recognition, named LRR-based Classification (LRRC). By the ideal that if each data class is linearly spanned by a subspace of unknown dimensions and the data are noiseless, the lowest-rank representations of a set of test vector samples with respect to a set of training vector...
In this paper we propose a hybrid approach for Content Based Image Retrieval that takes into account both global as well as local features of an image. Towards this, first Stationary Wavelet Transform is applied on query image to extract horizontal, vertical and diagonal detail matrices. Stationary Wavelet Transform is used because of its translational invariant property. After this global textural...
Content based image classification is a vital component of machine learning and is attaining increasing importance in the field of image processing. This paper has carried out widespread comparison of block truncation coding based techniques for feature vector extraction of images which is a precursor of image classification. A new block truncation coding (BTC) based technique using even and odd image...
This paper describes a new implementation of a mixture of techniques not used before for fingerprint recognition. The implementation consists of three stages: the location of the core, which is done through Radon transformation, the extraction of features (out of which a square fingerprint is produced with the core, and the center of the mass is obtained from it), in stage three, the resulting image...
In this paper, a specific region called affine noisy invariant region is extracted from a query and database images to help accurate retrieval on different attacks. Then, only a 64×1 codebook based feature vector is obtained from this specific region applying vector quantization and codebook generation based on the Linde-Buzo-Gray algorithm, which reduces retrieval feature comparison calculations...
Gait recognition is a new biometric identification technology. In this paper, we present a study and analysis in incorporating spatial and temporal feature matrix of gender classification based on human gait, which can increase the robustness of temporal gait feature. Gait period is obtained by locally linear embedding (LLE) algorithm. A different way based on Principal Component Analysis (PCA) to...
Several studies for palmprint-based personal identification have focused on improving the performance of palmprint images captured under visible light. However, during the past few years, some researchers have considered multispectral images to improve the effect of these systems. Compared with color images, multispectral images provide additional information due to its variety of spectral bands....
Fingerprints are the oldest and most widely used form of biometric identification. Uniqueness of one's Fingerprint remains same throughout the lifetime. Therefore, fingerprints are being used in many biometric systems such as civilian and commercial identification devices and forensic investigation systems. In our paper we have proposed a fingerprint recognition system as a combination of three significant...
The web contains enormous amount of information. From that enormous information only small amount of that information is visible to users and a huge portion of the information is not visible to the users. This is because traditional search engines are not able to index or access all information. The information which can be retrieved by following hypertext links are accessed by such traditional search...
Nowadays, biometrics is a research field in full expansion, several identification and verification systems are now developed, however their performances remain unsatisfactory facing to the growing security needs. Generally, the use of only one biometric decreases the reliability of these systems; thus, we have to combine several modalities. In this paper, we propose a multibiometric fusion approach...
This paper focuses on the research and development of a human resource management (HRM) system which is based on face authentication and RFID technology for more efficient security and reliability. In the proposed system, a user ID is first read from the given RFID tag to retrieve the corresponding records from the database to be used in the authentication process together with the user image which...
Machine vision is applied to detect wood knots and cracks, to classify strong and stable woods. In order to obtain effective and efficient classification a well-defined pattern recognition and feature extraction algorithms are essential. In this paper we examine three different methods for feature extraction; Gray level co-occurrence matrix (GLCM), Local binary patterns (LBP), and statistical moments...
This paper presents a system for detecting breast cancer based on moments. Instead of trying to improve the applied classifier we focused on improving the input attributes. We extracted new features from database samples using the first four moments namely, mean, variance, skewness and kurtosis. Through simulations, 10-fold cross validation method was applied to the Wisconsin breast cancer database...
Fingerprint matching is currently the subject of intense research by both private and academic institutions. So fingerprints are emerging as the most common and trusted biometric for personal identification. For the fingerprint matching problem, the input is some fingerprint images and the output is the probability that the fingerprints were captured from the same finger. This paper presents an improved...
In this paper, we propose a new approach for feature selection using fuzzy-ARTMAP classification and conflict characterization in fault diagnosis process. This approach is realized in two stages. In the first one, we classify the unfaulty functioning data of system using the fuzzy-ARTMAP classification. In the second stage, a conflict is accounted between features of test data based on the hyper-cubes...
This paper proposes a single image-based face liveness detection method for discriminating 2-D paper masks from the live faces. Still images taken from live faces and 2-D paper masks were found to bear the differences in terms of shape and detailedness. In order to effectively employ such differences, we exploit frequency and texture information by using power spectrum and Local Binary Pattern (LBP),...
Electro encephalogram (EEG) is a widely used tool for the clinical investigation of epileptic seizures. A new scheme of epileptic seizure detection using statistical features and Discrete Cosine Transform (DCT) is presented in this paper. Median absolute deviation (MAD) and variance is taken as the discriminating features between three different classes of EEG under study. The DCT was used for feature...
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