This paper describes an improved boosting algorithm, the MutualBoost algorithm, and its application in developing a fast and robust Gabor feature based face recognition system. The algorithm uses mutual information to eliminate redundancy among Gabor features selected using the AdaBoost algorithm. Selected Gabor features are then subjected to Generalized Discriminant Analysis (GDA) for class se...

This paper presents a model-based object recognition approach that uses a hierarchical Gabor wavelet representation. The key idea is to use magnitude, phase and frequency measures of Gabor wavelet representation in an innovative flexible matching approach that can provide robust recognition. A Gabor gr id , a topology-preserving map, eficiently encodes both signal energy and structural informat...

This paper deals with convolution setting at boundary regions for 1D convolution computed during recursive Gaussian and Gabor filtering as well as staged Gabor filtering computed more efficiently as modulation, recursive Gaussian, and demodulation. These are established fast approximations to their filters. Until recently, all the three applications of recursive filters suffered from distortion...

Examinations of the early vision system of mammals have shown Gabor-like behaviour of the simple cell responses. Furthermore, the advantages of Gabor-like image ltering are evident in computer vision. This causes strong demand to achieve Gabor-like responses in biology inspired spiking neural networks and so we propose a neural vision network based on spiking neurons with Gabor-like simple cell...

Gabor frames have been extensively studied in time-frequency analysis over the last 30 years. They are commonly used in science and engineering to synthesize signals from, or to decompose signals into, building blocks which are localized in time and frequency. This chapter contains a basic and self-contained introduction to Gabor frames on finite-dimensional complex vector spaces. In this setti...

This paper introduces a novel Gabor-Fisher (1936) 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 representation of face images. The novelty of this paper comes from 1) the derivation of an augmen...

This paper develops a novel face recognition technique called Complete Gabor Fisher Classifier (CGFC). Different from existing techniques that use Gabor filters for deriving the Gabor face representation, the proposed approach does not rely solely on Gabor magnitude information but effectively uses features computed based on Gabor phase information as well. It represents one of the few successf...

We present an independent Gabor features (IGFs) method and its application to face recognition. The novelty of the IGF method comes from 1) the derivation of independent Gabor features in the feature extraction stage and 2) the development of an IGF features-based probabilistic reasoning model (PRM) classification method in the pattern recognition stage. In particular, the IGF method first deri...

Gabor features are widely used in many computer vision applications such as image segmentation and pattern recognition. To extract Gabor features, a set of Gabor filters tuned to several different frequencies and orientations is utilized. The computational complexity of these features, due to their non-orthogonality, prevents their use in many real-time or near real-time tasks. Many research ef...