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Artificial neural network based classification of varieties of thin and thick fabric images

Basavaraj S Anami, Mahantesh C Elemmi

Abstract


Abstract: The proposed work focuses on classification of varieties of thin and thick fabric materials from images. The morphological operations such as erosion and dilation are performed. Morphological features namely, avg_moments, average_area, roundness, max_area, average_perimeter, average_eccentricity, circularity and average_equivalent_diameter are extracted. The prediction is carried out using artificial neural network. The classification rates of 84.84% and 90.90% are obtained for thin and thick fabric images. The classification rates for varieties of thin and thick fabric images are found to be 85.85% and 90.90% respectively.

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References:

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DOI: https://doi.org/10.37628/ijoippr.v4i1.357

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