Publication Type : Conference Paper
Publisher : 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS)
Source : 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS) (2020)
Url : https://ieeexplore.ieee.org/abstract/document/9074355
Keywords : Communication systems, Correlation, Cross Correlation, Databases, Euclidean distance, Gray-level co-occurrence matrix, Histograms, Image segmentation, Second order statistics, Texture Classification
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2020
Abstract : Classification refers to a physical object as being specified in a set of predefined categories. The goal in texture classification is to provide an unknown sample image for a set of known texture classes. It involves deciding which category of the texture of a painted image. Texture classification is a popular technique used in Image Processing Fields. Its applications includes classification from satellite images in types of land use, automated paint inspection for quality check, automated inspection of defects in the textile industry. In this paper texture classification is done using the gray level co-occurrence matrix. The gradient angle is used to obtain the structural component of the texture. Instead of finding the GLCM for all the angles, in this paper the GLCM of the maximum orientation is used to classify the textures. As a result the computational time and complexity have drastically reduced. Experimental analysis was performed by changing the parameters of the co-occurrence matrix and the gradient angle.
Cite this Research Publication : Sujee R. and Dr. Padmavathi S., “Fast Texture Classification using Gradient Histogram Method”, in 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), 2020.