Texture identification and matching a sample fabric with in a known collection of produced fabrics is a time-consuming and difficult process as a human activity. In this study, a computational method for texture textile identification is introduced using image analysis method. For this purpose, the fabrics images were captured by a digital flat scanner. The
texture features were extracted using Edge frequency method, in which a gradient for all pixels of the texture is computed and the texture features are defined as average values of gradient in specified distance and also Gray Level co-occurrence Matrix as a well-known method. In this way, a library of texture features was collected. To match a new texture with the library samples, the closest texture feature based on Euclidian distance was identified as the fabric texture. The experimental results with 33 different textures showed successful identification of textures with both of these methods however edge frequency method is more feasible and acceptable according to its computational simplicity and lower processing time. In addition, it was shown that the edge frequency method is well insensitive to the color and scanning direction (rotating the sample) of fabric.

Keywords: Texture, Textile, Knitted, Edge frequency, Gray level co-occurrence matrix.

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مدیر سایت چهارشنبه 4 اردیبهشت‌ماه سال 1392 ساعت 06:29 ق.ظ