Classification of Soil Textures Based on Laws Features Extracted from Preprocessing Images on Sequential and Random Windows

TLDR: The experimental results on various Soil textures clearly demonstrate the efficiency of the proposed methods, and the features are constructed on preprocessed methods applied on the Soil texture image by considering different types of windows.

Abstract: Texture analysis has been used for recognizing synthetic and natural textures. Textures are one of the important features in computer vision for image classification and retrieval. An important approach to region description is to quantify its texture content. In this paper ,the Soil images has been analyzed using various image pre processing tasks such as Gray level thresholding, Low pass filter, Edge enhancement using Prewitt's Horizontal filtering and then Feature extraction using 3x3 Law's mask convolution. The features are constructed on preprocessed methods applied on the Soil texture image by considering different types of windows. These features offer a better classification rate. The experimental results on various Soil textures clearly demonstrate the efficiency of the proposed methods.