Image Processing Based Production Flaw Detection in Knitting
J. Ramprabu1, Aswini N2
1J. Ramprabu, Assistant Professor II, Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
2Aswini N, Department of Electrical and Electronics Engineering, Kumaraguru College of Technology, Coimbatore (Tamil Nadu), India.
Manuscript received on 28 September 2019 | Revised Manuscript received on 10 November 2019 | Manuscript Published on 22 November 2019 | PP: 1123-1128 | Volume-8 Issue-6S3 September 2019 | Retrieval Number: F11860986S319/19©BEIESP | DOI: 10.35940/ijeat.F1186.0986S319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: One of the major problems in production is that the number of faults occurred while producing a fabric, since it directly influences productivity. To overcome the losses, this paper provides a system with special surveillance to detect the knitting process, identify and locate faults during manufacturing, by inspecting the fabric. The system also gives the user a valuable set of data related with production. This examination has demonstrated that picture handling can possibly give solid estimations to recognizing abandons in sewed textures. On-line texture deformity location was tried consequently by contrasting texture pictures caught by a computerized camera. In this way, it is demonstrated that the created picture catching and investigation framework is equipped for halting the round sewing machine by utilizing processor when a deformity is caught by the web camera.
Keywords: Image Processing, Circular Knitting Machine, Web Camera.
Scope of the Article: Image analysis and Processing