In industrial applications, product identification is the most common thing now days. To kept in mind that we focus on the classification of our industrial product with the help of its texture using segmentation [7] and offset. Texture plays an important role in identifying the characteristics of an image/product. Image has visual features which are characterized as: (i) domain specific feature...

As digital images become more widely used, digital image analysis must find more tools to work on them. Texture analysis is a huge challenge nowadays, since simple images may be considered as a mosaic of textures separated by some boundaries. That is why both texture retrieval and classification, combined with image segmentation, may be very powerful in image analysis. Texture retrieval (ie. to...

Texture compression is a specialized form of image compression designed for storing texture maps in 3D computer graphics rendering systems. Texture compression is an important technique in graphics processing units (GPUs) for saving memory bandwidth. Unlike conventional image compression algorithms, texture compression algorithms are optimized for random access. Therefore, the variable-rate seq...

The problem that the Markov random field (MRF) model captures the structural as well as the stochastic textures for remote sensing image segmentation is considered. As the one-point clique, namely, the external field, reflects the priori knowledge of the relative likelihood of the different region types which is often unknown, one would like to consider only two-pairwise clique in the texture. ...

T exture analysis is the extraction of textural features from images (Tuceryan and Jain, 1998). The meaning of texture varies, depending on the area of science in which it is used. In general, texture refers to the physical character of an object or the appearance of an image. In image analysis, texture is defined as a function of the spatial variation in intensities of pixels (Tuceryan and Jai...

Texture information plays an important role in image analysis. Although several descriptors have been proposed to extract and analyze texture, the development of automatic systems for image interpretation and object recognition is a difficult task due to the complex aspects of texture. Scale is an important information in texture analysis, since a same texture can be perceived as different text...

Texture analysis refers to the branch of imaging science that is concerned with the description of characteristic image properties by textural features. However, there is no universally agreed-upon definition of what image texture is and in general different researchers use different definitions depending upon the particular area of application (Tuceryan & Jain, 1998). In this chapter texture i...

Retrieval of an image is a more effective and efficient for managing extensive image database. Content Based Image Retrieval (CBIR) is a one of the image retrieval technique which uses user visual features of an image such as color, shape, and texture features etc. It permits the end user to give a query image in order to retrieve the stored images in database according to their similarity to t...

Multi-view image coding benefits from knowledge of the depicted scene’s 3-D geometry. To exploit geometry information for compression, two different approaches can be distinguished. In texture-based coding, images are converted to texture maps prior to compression. In image-based predictive coding, geometry is used for disparity compensation and occlusion detection between images. Coding perfor...