We propose a novel human face recognition approach in this paper, based on two-dimensional Gabor filtering and supervised classification. The feature extraction technique proposed in this article uses 2D Gabor filter banks and produces robust 3D face feature vectors. A supervised classifier, using minimum average distances, is developed for these vectors.… (More)
recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification method uses a special nonlinear metric, derived from the Hausdorff distance for sets, and a minimum mean distance classifier.
An automatic multiple person detection and tracking technique for static camera movies is proposed in this paper. First, a moving human identification method is provided. It detects the video objects by using a novel temporal differencing based algorithm and some morphological processes. Then, our approach decides which moving objects represent walking… (More)
In this paper, we propose an automatic unsupervised classification technique. The method works successfully for any kind of feature vectors, therefore we insist on classification step of recognition process only. First we propose an semiautomatic unsupervised classification approach, based on region-growing method. Then, by eliminating the condition of… (More)
The objective of the present paper is to describe a pattern recognition approach for image segmentation. First, in the introduction, we describe the general aspects of uniformity and texture recognition. Then we provide a mean-based feature extraction approach for uniformity analysis and a moment-based one for texture analysis. In the classification stage… (More)