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The research of facial beauty is an interdisciplinary topic involved in psychology, aesthetics, computer version and machine learning. In this paper, we propose several methods to assess facial beauty under unconstrained conditions. Our main works are as follows: First, we apply the local binary pattern (LBP) descriptor in different bins for face representation. We tried different types of LBP methods...
Down syndrome, the most prevalent chromosome disorder in mankind, occurs approximately in one per thousand infants born per a year. Also, life expectancy of people suffering from this irregularity has increased from 25 to 59 in the last decades. Recognizing such patients in critical and high security places like security gates could assist responsible people to make proper decisions. This irregularity...
Facial expressions are the most informative activities on the human face. Facial movements can be analyzed in order to recognize facial expressions. These movements are extracted using the facial geometry or texture. The paper addresses the facial expression recognition based on Local Binary Patterns (LBP) extracted from the texture information. The LBP operator and its extensions are applied to different...
A novel approach to facial expression recognition based on the combination of local binary pattern (LBP) and Adaboost is proposed. Firstly, facial expression images are processed with LBP operator, which can eliminate the effect of environment lighting in a certain extent and has the powerful capability of texture feature description. And then facial expression features are presented with LBP histograms...
This paper describes an image-based system to detect spoof fingerprint attacks in fingerprint biometric systems. It is based on the observation that, real and spoof fingerprints exhibit different textural characteristics. These are based on structural, orientation, roughness, smoothness and regularity differences of diverse regions in a fingerprint image. Local binary pattern (LBP) histograms are...
Two main restrictions exist in state-of-the-art text detection algorithms: 1. Illumination variance; 2. Text-background contrast variance. This paper presents a robust text characterization approach based on local Haar binary pattern (LHBP) to address these problems. Based on LHBP, a coarse-to-fine detection framework is presented to precisely locate text lines in scene images. Firstly, threshold-restricted...
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