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Contactless fingerprint recognition systems are being researched in order to reduce intrinsic limitations of traditional biometric acquisition technologies, encompassing the release of latent fingerprints on the sensor platen, non-linear spatial distortions in the captured samples, and relevant image differences with respect to the moisture level and pressure of the fingertip on the sensor surface.
Author identification is the process of recognizing an author based on a sample of text. Feature selection is the process of selecting the most salient features required for recognition. In many cases, this results in an increase in recognition accuracy. In this paper, we apply Genetic and Evolutionary Feature Selection with Machine Learning (GEFeSML) to author identification. We then introduce Genetic...
In this paper, a method for performing semiautomatic identity label annotation on facial images, obtained from monocular and stereoscopic videos is introduced. The proposed method exploits prior information for the data structure, obtained from the application of a clustering algorithm, for the selection of the facial images from which label inference should begin. Then, a sparse graph is constructed...
Image enhancement is one of the pre-processing steps of fingerprint image processing, in which an image can be viewed with clear ridge and valley patterns. This paper presents a novel image enhancement method using Modified Histogram Equalization (MHE) based on the Adaptive Inverse Hyperbolic Tangent (AIHT) method. The algorithm was developed in the Texas Instruments CCS environment and implemented...
In this paper, we propose a person identification method exploiting human motion information. A Self Organizing Neural Network is employed in order to determine a topographic map of representative human body poses. Fuzzy Vector Quantization is applied to the human body poses appearing in a video in order to obtain a compact video representation, that will be used for person identification and action...
Facial expressions result from movements of muscular action units, in response to internal emotion states or perceptions, and it has been shown that they decrease the performance of face-based biometric recognition techniques. This paper focuses in the recognition of facial expressions and has the following purposes: 1) confirm the suitability of using dense image descriptors widely known in biometrics...
This paper proposes a technique for face feature extraction using sinusoidal projection. Essentially, the technique uses a projection matrix, which is formed by stacking vectors with sinusoidal values at different frequencies, to directly multiply with raw image matrix for weighted feature extraction. Orthogonality among vectors within the sinusoidal projection matrix is observed when the frequencies...
In this paper we have proposed a unique approach for face recognition based on modular Independent Component Analysis (ICA) with local facial features. The face images are segmented based on skin color using YCbCr color space. In this research work we have considered the samples of individual person which consist of sufficient number of images having pose variations, facial expressions and changes...
There are still many challenging problems in facial gender recognition which is mainly due to the complex variances of face appearance. Although there has been tremendous research effort to develop robust gender recognition over the past decade, none has explicitly exploited the domain knowledge about the appearance difference between male and female. Beard/mustache contributes substantially to the...
Classical face detection algorithm works on only near frontal faces. Extending it to other poses and in-plane rotated faces require separately trained classifiers which increases both the training and processing time. We solve this instead by developing a reference model that is capable of detecting upright faces in various poses. Then a probabilistic framework is used to estimate occurrence of in-plane...
This paper presents a classification analysis of gait biometric on twins and non-twins siblings. The aim of this paper is to investigate the existence or inexistence of similarity in the gait of twins and compare it to the gait of non-twins siblings. The motivation behind this paper is that a video-based surveillance system may not be able to rely on face biometric alone when dealing with twins. The...
Genetic and Evolutionary Feature Extraction (GEFE), introduced by Shelton et al. [1], [2], [3], use genetic and evolutionary computation to evolve Local Binary Pattern (LBP) based feature extractors for facial recognition. In this paper, we use GEFE in an effort to classify male and female Drosophila melanogaster by the texture of their wings. To our knowledge, gender classification of the drosophila...
The periocular region has recently emerged as a promising trait for unconstrained biometric recognition, specially on cases where neither the iris and a full facial picture can be obtained. Previous studies concluded that the regions in the vicinity of the human eye - the periocular region- have surprisingly high discriminating ability between individuals, are relatively permanent and easily acquired...
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