In this paper we propose a face recognition system based on local features. Interesting feature points in the face image are located by Gabor filters, which gives us an automatic system that is not dependent on accurate detection of facial features. The feature points are typically located at positions with high information content (such as facial features), and at each of these positions we ex...

In this paper we propose a biometric face recognition system based on local features. Informative feature locations in the face image are located by Gabor filters, which gives us an automatic system that is not dependent on accurate detection of facial features. The feature locations are typically located at positions with high information content (such as facial features), and at each of these...

Gabor filters have been successfully employed in texture segmentation problems, yet a general multi-filter multi-texture Gabor filter design procedure has not been offered. To this end, we first present a multichannel paradigm that provides a mathematical framework for the design of the filters. The paradigm establishes relationships between the predicted texture-segmentation error, the power s...

This paper presents an efficient face recognition system which can handle partial occlusion in both training and test image sets. We hybridize Gabor filter with Eigen faces which make use of localization effect of Gabor filter and whole appearance effect of Eigen faces. It has been tested on AR database which contains naturally occluded face images.

In this paper, we present a new approach for face recognition system. The method is based on 2D face image features using subset of non-correlated and Orthogonal Gabor Filters instead of using the whole Gabor Filter Bank, then compressing the output feature vector using Linear Discriminant Analysis (LDA). The face image has been enhanced using multi stage image processing technique to normalize...

ses a facial expression recognition system based on Gabor feature using a novel r bank. Traditionally, a global Gabor filter bank with 5 frequencies and 8 ten used to extract the Gabor feature. A lot of time will be involved to extract mensions of such Gabor feature vector are prohibitively high. A novel local Gabor art of frequency and orientation parameters is proposed. In order to evaluate t...

This research presents the multi –modal biometric system for iris and fingerprint This paper presents the Feature level fusion using wavelet for combining two unimodal biometric system. Gabor transform is used for feature extraction and wavelet transformation for fusion of iris and fingerprint. The system applied artificial neural network technique for recognizing whether the user is genuine (a...

This paper proposes a multimodal biometric system through Gaussian Mixture Model (GMM) for face and ear biometrics with belief fusion of the estimated scores characterized by Gabor responses and the proposed fusion is accomplished by Dempster-Shafer (DS) decision theory. Face and ear images are convolved with Gabor wavelet filters to extracts spatially enhanced Gabor facial features and Gabor e...

We present an object recognition architecture based on feature extraction by Gabor filter kernels and feature classification by an artificial neural network. The parameters of the Gabor filters are optimized to the specific problem by minimizing an energy function. Such Gabor filters extract features that can be more easily classified by the neural network. Moreover the feature space is low-dim...