• Manoj P. Patil

Image-based fabric understanding can help to develop new methods for fabric classification and understandings. Automatic recognition of fabric types deals with understanding material using color and texture features. In this paper the RGB color properties and texture using Gray Level co-occurrence Matrix(GLCM) are extracted and used for classification using k nearest neighbor(k-NN) algorithm. The experiments are carried out with variation in the value of neighbors and feature combinations. The RGB color features alongwith GLCM based texture feature gives 69.45% accuracy. The five nearest neighbors need to be computed to get highest accuracy.

Fabric identification, GLCM, Nearest Neighbor

"Automatic Fabric Identification using Color and GLCM based texture features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.c796-c800, May-2022, Available :http://www.jetir.org/papers/JETIR2205404.pdf

"Automatic Fabric Identification using Color and GLCM based texture features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppc796-c800, May-2022, Available at : http://www.jetir.org/papers/JETIR2205404.pdf