Texture Analysis Based on the Gray-level Co-occurrence Matrix Considering Possible Orientations

Texture is literally defined as consistency of a substance or a surface. Technically, it is the pattern of information or arrangement of structure found in an image. Texture is a crucial characteristic of many image type and textural features have a plethora of application viz., image processing, remote sensing, content-based imaged retrieval and so on. There are various ways of extracting these features and the most common way is by using a gray-level cooccurrence matrix (GLCM). GLCM contains second order statistical information of neighbouring pixels of an image. In the present work, a detailed study on a sample image (8 bit gray scale image) pattern is carried out with an aim to develop a methodology that acts as a non destructive and contactless way of describing the surface texture. The study involves the use of a contemporary method, known as absolute value of differences (AVD) when the information of the image is not present in higher frequency domain. The simulated results show that AVD can be used as an alternative to the classical inertia of moment (IM) computing and directions do matter while GLCM processing on image pattern. Moreover it is shown that Sobel edge-detector operator along with GLCM may be used to predict the surface texture quantitatively.