This paper describes the usage of geoetic algorithms as feature selectors in a texture classification system. This is part of a system developed within a research project concerning the classification of genuine texture. An attempt is made to underline why an automised feature selector is a useful part of the texture classification system. Furthermore the way of including the genetic algorithms...

We have carried out a detailed evaluation of the use of texture features in a query-by-example approach to image retrieval. We used 3 radically different texture feature types motivated by i) statistical, ii) psychological and iii) signal processing points of view. The features were evaluated and tested on retrieval tasks from the Corel and TRECVID2003 image collections. For the latter we also ...

Texture synthesis techniques require nearly uniform texture samples, however identifying suitable texture samples in an image requires significant data preprocessing. To eliminate this work, we introduce a fully automatic pipeline to detect dominant texture samples based on a manifold generated using the diffusion distance. We define the characteristics of dominant texture and three different t...

A new multi-feature fusion technique based on Dempster-Shafer's evidential reasoning for classification of image texture is presented. The proposed technique is divided into three main steps. In the first step, the fractal dimension and gray co-occurrence matrix entropy are extracted from a texture image. In the second step, we focus on how to design a probability assignment function m(A) repre...

In this report, we propose a wavelet-based content descriptor with which we implement an image retrieval system. Initially, we propose the wavelet-based weighted standard deviation texture descriptor. We then show how to extend this descriptor to characterize both texture and color in images. Thus, we obtain a compact feature vector that characterizes images in terms of both texture and color. ...

Based on human visual attention mechanism and texture visual perception, this paper proposes a method for man-made object detection by extracting texture and geometry structure features. Followed by clustering the texture feature, geometry structure feature is obtained to realize final detection. Then a man-made object detection scheme is designed, by which typical man-made objects in complex n...

As a regional feature, texture is a description of the spatial distribution of the image pixels. As texture can fully utilize the image information, it can become an important basis to describe and recognize the image. Compared with other image features, texture can take both the macro image properties and micro structure into consideration; therefore, feature has become a significant feature t...

This paper introduces an innovative method, Dynamic Local Feature Analysis (DLFA), for human face recognition. In our proposed method, the face shape and the facial texture information are combined together by using the Local Feature Analysis (LFA) technique. The shape information is obtained by using our proposed adaptive edge detecting method that can reduce the effect on different lighting c...

In order to improve the recognition accuracy of cucumber diseased image, a new method based on image preprocessing and extraction of texture feature had been proposed, which making full use of color information included in cucumber image. At first, vector median filter for color images was applied to remove noise, and then chromaticity moments were extracted as texture feature. Experimental res...

This paper proposes, a hybrid approach employing texture and colour feature is investigated. A modified approach for performing texture based feature extraction by gray level co-occurrence matrix and colour based feature extraction by colour cooccurrence vector. The Euclidean distance classifier is used for finding the similarity measures between the query image and the database image. In our p...