... This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights

Abstruct- A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a

We present a novel statistical and variational approach to image segmentation based on a new algorithm named region competition. This algorithm is derived by minimizing a generalized Bayes/MDL criterion using the variational principle. The algorithm is guaranteed to converge to a local minimum

feature representation and extraction, multidimensional indexing, and system design, three of the fundamental bases of content-based image retrieval. Furthermore, based on the state-of-the-art technology available now and the demand from real-world applications, open research issues are identified

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crucial step in developing such systems is how to determine the minimal number of spectral bands and select the most representative bands to build the multispectral imaging system. This paper presents preliminary studies on feature band selection by analyzing hyperspectral palmprint data (420nm~1100nm

the region of interest (ROI), then constructed a set of Gabor filters to get ROI eigenvectors, combined with the palm images ’ invariant moment features together as the input of the neural network to train and recognize. Experiments show that the method is effective. Index Terms—palmprint recognition, Gabor

This paper introduces a novel Gabor-Fisher Classifier (GFC) for face recognition. The GFC method, which is robust to changes in illumination and facial expression, applies the Enhanced Fisher linear discriminant Model (EFM) to an augmented Gabor feature vector derived from the Gabor wavelet

Abstract—We introduce a new general framework for the recognition of complex visual scenes, which is motivated by biology: We describe a hierarchical system that closely follows the organization of visual cortex and builds an increasingly complex and invariant feature representation by alternating

the most representative bands to build the system. This paper presents a study on feature band selection by analyzing hyper-spectral palmprint data (520–1050 nm). Our experimental results showed that three spectral bands could provide most of the discriminate informa-tion of a palmprint. This finding could