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Online Sewing Defect Monitoring for SNLS Machine by Image Processing Technique


Affiliations
1 Department. of Textile Technology, Department. of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore-641049, India
     

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Apparels are subjected to visual examination to detect sewing defects after making of the garments which results in higher rejection, time, cost etc. Sewing defects must be detected early i.e during sewing itself and accurately to overcome above quality issues. Apparels are mostly sewn with lock stitch in straight and curve directions, with different colours and stitches per inch. The paper discuss the on line detection of sewing defects occurring during the sewing process. Common defects such as skipped stitch, missed stitch, or loose stitch occurring in lockstitch are detected and marked. Using image processing methods, the proposed work follows the stitch path by capturing digital images of stich lines in lock stitch sewing machine and processed through PYTHON software to detect the sewing defects and subsequently stop the machine during sewing.

Keywords

Sewing, Defect, Online, Image Processing, SNLS.
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  • Online Sewing Defect Monitoring for SNLS Machine by Image Processing Technique

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Authors

V. Ramesh Babu
Department. of Textile Technology, Department. of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore-641049, India
B. Karunamoorthy
Department. of Textile Technology, Department. of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore-641049, India

Abstract


Apparels are subjected to visual examination to detect sewing defects after making of the garments which results in higher rejection, time, cost etc. Sewing defects must be detected early i.e during sewing itself and accurately to overcome above quality issues. Apparels are mostly sewn with lock stitch in straight and curve directions, with different colours and stitches per inch. The paper discuss the on line detection of sewing defects occurring during the sewing process. Common defects such as skipped stitch, missed stitch, or loose stitch occurring in lockstitch are detected and marked. Using image processing methods, the proposed work follows the stitch path by capturing digital images of stich lines in lock stitch sewing machine and processed through PYTHON software to detect the sewing defects and subsequently stop the machine during sewing.

Keywords


Sewing, Defect, Online, Image Processing, SNLS.

References