Abstract
Classification of texture is a very tedious problem in computer vision and pattern recognition. In this problem, the material is assigned to particular class of texture using its properties. This paper used both color and texture features to improve the recognition performance of Flickr Material Database (FMD). Authors described method of combining Color features (RGB), Luminance and Texture features. Gray-Level Co-occurrence Matrix (GLCM) is used to extract Texture features. The classification using, K-Nearest Neighbors (KNN) classifier is discussed with the experimental results.
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Sapkale, S.S., Patil, M.P. (2019). Material Classification Using Color and Texture Features. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1035. Springer, Singapore. https://doi.org/10.1007/978-981-13-9181-1_5
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