Linear independent component analysis (ICA) learns simple cell receptive fields fromnatural images.Here,we show that linear complexvalued ICA learns complex cell properties from Fourier-transformed natural images, i.e. two Gabor-like filters with quadrature-phase relationship. Conventional methods for complex-valued ICA assume that the phases of the output signals have uniform distribution. We ...

More and more research have been developed very recently for automatic hand recognition. This paper proposes a new method for contactless hand authentication in complex images. Our system uses skin color and hand shape information for hand detection process. Next, the palm is extracted and characterized by circular Gabor filter. Finally, the palm features are matched by a new normalized approxi...

A novel type of feature extraction is introduced to be used as a front end for automatic speech recognition (ASR). Two-dimensional Gabor filter functions are applied to a spectro-temporal representation formed by columns of primary feature vectors. The filter shape is motivated by recent findings in neurophysiology and psychoacoustics which revealed sensitivity towards complex spectro-temporal ...

In this paper, we employ a new adaptive basis of functions — brushlets for extracting texture properties. Brushlets are functions which are well localized with only one peak in the frequency domain. Hence, a representation of texture in terms of spatial frequency distributions can be constructed. The Brushlet features are used in texture image retrieval experiments to assess its effectiveness b...

Face recognition is an active research work since its use is widespread in many applications. The proposed work is to develop a hybrid illumination pre-processing method for face recognition by combining two-dimensional Discrete Wavelet Transform (2D DWT) and Contrast Limited Adaptive Histogram Equalization (CLAHE). 2D DWT is applied on the original image and the LL sub-band of DWT coefficients...

Content Based Image Retrieval (CBIR) is now a widely investigated issue that aims at allowing users of multimedia information systems to automatically retrieve images coherent with a sample image. A way to achieve this goal is the computation of image features such as the color, texture, shape, and position of objects within images, and the use of those features as query terms. We propose to us...

Local Gabor features (jets) have been widely used in face recognition systems. Once the sets of jets have been extracted from the two faces to be compared, a proper measure of similarity (or distance) between corresponding features should be chosen. For instance, in the well known Elastic Bunch Graph Matching (EBGM) approach and other Gabor-based face recognition systems, the cosine distance wa...

Feature extraction and classification using Gabor wavelets have proven to be successful in computer vision and pattern recognition. Gabor feature based Elastic Bunch Graph Matching (EBGM), which demonstrated excellent performance in the FERET evaluation test, has been considered as one of the best algorithms for face recognition due to its robustness against expression, illumination and pose va...

This paper proposes an algorithm for segmentation and extracting an object region by using Gabor filters. Gabor filters are exploited to extract spatial frequency in some orientations, and not only the outputs of Gabor filters but also color informations are used to construct the features at each image pixel. The criterion is devised so as to consider the similarity, the region size and the reg...

This paper introduces several novel Gabor-based local, shape and color features for image classification. First, a new Gabor-HOG (GHOG) descriptor is proposed for image feature extraction by concatenating the Histograms of Oriented Gradients (HOG) of all the local Gabor filtered images. The GHOG descriptor is then further assessed in six different color spaces to measure classification performa...