%0 Journal Article
%T New Brodatz-Based Image Databases for Grayscale Color and Multiband Texture Analysis
%A Safia Abdelmounaime
%A He Dong-Chen
%J ISRN Machine Vision
%D 2013
%R 10.1155/2013/876386
%X Grayscale and color textures can have spectral informative content. This spectral information coexists with the grayscale or chromatic spatial pattern that characterizes the texture. This informative and nontextural spectral content can be a source of confusion for rigorous evaluations of the intrinsic textural performance of texture methods. In this paper, we used basic image processing tools to develop a new class of textures in which texture information is the only source of discrimination. Spectral information in this new class of textures contributes only to form texture. The textures are grouped into two databases. The first is the Normalized Brodatz Texture database (NBT) which is a collection of grayscale images. The second is the Multiband Texture (MBT) database which is a collection of color texture images. Thus, this new class of textures is ideal for rigorous comparisons between texture analysis methods based only on their intrinsic performance on texture characterization. 1. Introduction It has long been argued that texture plays a key role in computer-based pattern recognition. Texture can be the only effective way to discriminate between different surfaces that have similar spectral characteristics [1¨C6]. Texture was early recognized as mainly a spatial distribution of tonal variations in the same band [7]. Different grayscale texture methods have been proposed based on different techniques [7¨C12]. For an objective and rigorous comparison between different texture analysis methods, it is important to use standard databases [13, 14]. The standard Brodatz grayscale texture album [15] has been widely used as a validation dataset [16, 17]. It is composed of 112 grayscale images representing a large variety of natural grayscale textures. This database has been used with different levels of complexity in texture classification [18], texture segmentation [19], and image retrieval [20]. A rotation invariant version of the Brodatz database was also proposed [21] and used for texture classification and retrieval [22, 23]. Recently, we have seen a growing interest in color texture [24]. This is a natural evolution of the field of texture, from grayscale to color texture. The use of color in texture analysis showed several benefits [25¨C27]. In color texture, efforts have been made to find efficient methods to combine color and texture features [24]. Consequently, the evaluation of color texture methods requires images in which color and texture information are both sources of discriminative information. Many color texture databases have been proposed
%U http://www.hindawi.com/journals/isrn.machine.vision/2013/876386/