The two-dimensional Gabor function is adapted to natural image statistics by learning the joint distribution of the Gabor function parameters. The joint distribution is then approximated to yield an analytical model of simple-cell receptive fields. Adapting a basis of Gabor functions is found to take an order of magnitude less computation than learning an equivalent non-parameterized basis. Der...

In this paper we focus on the great outburst of Gabor-based methods for face biometrics occurred in the last few years. Analytical approaches rely on the representation of a face with the Gabor responses computed on specific landmarks, while holistic methods take into account the face as a whole. We explore the role played by Gabor wavelets in international competitions, such as FERET or BANCA,...

Gabor schemes of multiscale image representation are useful in many computer vision applications. However, the classic Gabor expansion is computationally expensive due to the lack of orthogonality of Gabor functions. Some alternative schemes, based on the application of a bank of Gabor filters, have important advantages such as computational efficiency and robustness, at the cost of redundancy ...

As the Gabor filters are direction dependent, the Gabor transform of an image is to be performed for all chosen directions. Thus the set of angles used in Gabor feature extraction does affect the results in applications such as Content Based Image Retrieval (CBIR). In the present work, we modify the Gabor filter suitably in such a way that the modified function besides being free from the choic...

Gabor features has been recognized as one of the most successful representation methods, such as Elastic Graph Matching, Gabor Fisher Classifier, and AdaBoost Gabor Fisher Classifier. One of the key issues in using Gabor features is how to efficiently reduce its high dimensionality. This paper proposes a multiple Fisher classifiers combination approach based on re-grouping Gabor features select...

Gabor filters have long been proposed as models for spectro-temporal receptive fields (STRFs), with their specific spectral and temporal rate of modulation qualitatively replicating characteristics of STRF filters estimated from responses to auditory stimuli in physiological data. The present study builds on the Gabor-STRF model by proposing a methodology to quantitatively decompose STRFs into ...

This paper addresses new face recognition method based on Independent Component Analysis(1CA) and Gabor filter. Our method consists of three parts. The first part is Gabor filtering on predefined fiducial points that could represent robust facial features from original face image. The second part is transforming the facial features into the basis space of ICA, which is able to represent individ...

identification based on faces is still a useful method for many applications and face recognition developing is an active research field. in this paper, a novel face identification method is proposed. the proposed method (bridle path on gabor phase (bpgp)) is based on extracting texture patterns from phases of the gabor wavelet. also, in order to describe the textures, a novel texture descripto...

This thesis presents Gabor frames for L2(T) and for the space of periodic sequences Cp , as being analogue to Fourier series and the discrete Fourier transform. Results from the standard theory of Gabor frames for L2(R) are transferred to the periodic setting. This includes results about sampling Gabor systems and existence of Gabor frames. The interrelation of Gabor frames for the continuous s...