Identification of Land and Water Regions in a Satellite Image: A Texture Based Approach

Vision is the most important resource of information for human beings which contain several activities. Amongst these activities, object recognition and classification are widely used. Although, images are representation of vision which can be interpreted by machines, some images often do not exhibit regions of uniform intensity, but these images may contain variation of intensities which form certain repeated patterns. These repeated patterns are known as visual texture. These patterns can be the result of physical surface properties such as roughness, reflectance and color difference of surface. This special variation in pixel intensities is useful in a variety of applications. One such application is analysis of satellite images, whose purpose is to identify various regions in a given image. In this paper we try to exploit knowledge of texture i.e. repeated patterns of non uniform intensity, to recognize regions in the satellite images. There are many approaches used for texture analysis, mainly these are categorized as statistical, structural, filter and model based. In statistical approaches, a GLCM approach is used to find various regions i.e. land and water in a satellite image by extracting its texture information. KeywordsTexture, Satellite Images, GLCM, Clustering.