Choosing clothes with complex patterns and colors is a challenging task for visually impaired and blind people. The automatic clothing pattern and color recognition is also a challenging problem due to the large intra-class variation, rotation, scaling and illumination. Here, we recognize clothing patterns in four categories (plaid, striped, pattern-less, and irregular), and identify 11 clothing colors (red, orange, yellow, green, cyan, blue, purple, pink, black, grey, and white). The clothing patterns and colors are described to blind users verbally. To recognize clothing patterns, we propose a novel radon signature descriptor and a schema to extract statistical properties from wavelet sub-bands to capture global features of clothing patterns. They are combined with local features to recognize complex clothing patterns. To evaluate the effectiveness of the proposed approach, we used the clothing pattern image.Keywords: Radon signature, scale invariant feature transform, discrete wavele transform, wavelet analysisCite this Article Honey Mishra, Ashish Dewangan. Recognition and Classification of Clothing Pattern and Color. Recent Trends in Electronic and Communication Systems. 2016; 3(2): 33–41p.
