Texture Image Retrieval Using Fourier Transform
Abdelhamid Abdesselam · 2009
Abstract— Texture is an important visual property that characterizes a wide range of natural and artificial images which makes it a useful feature for retrieving images. During the last decades, several approaches have been proposed to describe the texture contents of an image. In early research works, texture descriptors were mainly extracted from the pixel space itself, edge histograms and co-occurrence-based features, are examples of such descriptors. Later on, dual spaces (transform of pixel space) such as frequency space or spaces resulting from Gabor and wavelet transforms were explored for texture characterization. This paper describes a Fourier- based technique for characterizing image textures. The performance of the technique is compared with several Fourier- and wavelet-based methods described in literature. The two main criteria that were used in this comparison are the accuracy and execution time of the techniques. simpler and faster. As a consequence, wavelet-based approaches gained much more popularity among the computer vision community. Fourier transform has also been widely used in characterizing textures. One of the reasons for that is its suitability for describing periodic functions such as texture images which usually contain quasi-repetitive patterns. Concentrations of Fourier power spectrum values capture dominant orientations of the patterns in the image and their distribution in the frequency space is closely related to coarseness of the texture (5, 6). These two features (directionality and coarseness of a texture) are of importance in texture analysis (17). The main drawback of using Fourier transform is the poor spatial localization it provides. Windowed Fourier transform has been introduced to overcome this problem at the cost of a significant increase in the computations (18). In this paper we describe a Fourier-based method for characterizing texture images and show that it performs better than many of the recently proposed techniques for texture characterization. We have included in our comparative study several Fourier- and wavelet-based texture characterization techniques. The two main criteria that were used in this comparison are the accuracy and running time of the techniques.