• Sainath Chilkuri
• Himanshukumar Prajapati
• Pankajkumar Purohit
• Kanchan Dabre

Textile fabric automation and manufacturing has been of great concern over the past decade. This is an interesting task due to the accidental changes of cloth material properties. Due to the increasing demand of consumers for high-quality textile products, an automatic and objective evaluation of the material texture appearance is important with reference to geometric structure characteristics, surface, and mechanical properties. The precise measurement of the material texture parameters, like weave structure and yarn counts find wide applications within the textile industry. The weave pattern and therefore the yarn count are analysed and determined for computer simulated sample images and also for the scanned real fabric images. Image Processing algorithms are used to identify the accurate structure of the woven fabric and to determine the yarn count. They are used for segmenting the crossed areas of yarns and also to detect the defects like crossed area thanks to the random distribution of yarns. Grey Scale Algorithm is applied to convert the fabric image into a grey level image. Histogram Equalization is used to enhance the contrast. Spatial Domain Projection to individually recognize the each pixels in a fabric.

Image Processing, Grey Scale Algorithm, Histogram Equalization, Spatial Domain Projection.

"Fabric Texture Analysis Using Image Processing Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 3, page no.392-397, March-2020, Available :http://www.jetir.org/papers/JETIR2003362.pdf

"Fabric Texture Analysis Using Image Processing Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 3, page no. pp392-397, March-2020, Available at : http://www.jetir.org/papers/JETIR2003362.pdf