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The new framework proposed in this paper provides an insight into the problem of face authentication (verification) in unconstrained environment. This unconventional method extracts and represents the microstructures and local features of a given face image by greedy approach and sparse code respectively. This gives a stable and discriminative local descriptor for each patch that hinge on the local...
An innovative approach based on local components called Optimal Random Image Component Selection is presented in this paper. Here, features are extracted from the Optimal Random Image Components by Gabor wavelets using greedy approach is proposed. These feature vectors are then down-sampled to some size which is then classified based on minimum distance measure. The design of Gabor filters for facial...
This paper presents a memetic algorithm based new approach to feature selection in face recognition. In this work, principal component analysis (PCA) has been used for dimensionality reduction/feature extraction and memetic algorithms have been applied for selection of features in face recognition application. ORL face database has been used for performing the experiments. The results indicate that...
Face recognition and expression analysis is one of the most challenging research areas in the field of computer vision. Even though face exhibits different facial expressions, which can be instantly recognized by human eyes, it is very difficult for a computer to extract and use the information content from these expressions. In this paper we present a method to analyze facial expression by focusing...
Pattern recognition problem rely on the features inherent in the pattern of images. Face detection and recognition is one of the challenging research areas in the field of computer vision. In this paper, we present a method to identify skin pixels from still and video images using skin color. Face regions are identified from this skin pixel region. Facial features such as eyes, nose and mouth are...
Face recognition has always been a fascinating research area. It has drawn the attention of many researchers because of its various potential applications such as security systems, entertainment, criminal identification etc. Many supervised and unsupervised learning techniques have been reported so far. Principal component analysis (PCA) is a classical and successful method for face recognition. Self...
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