SMT Component Inspection in PCBA’s using Image Processing Techniques
Anitha D B1, Mahesh Rao2
1Anitha D B, ECE Department, VVIET and Research Scholar, MRF, Mysore, India.
2Mahesh Rao, ECE Department, MIT, Mysore, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 25 September, 2019. | Manuscript published on October 10, 2019. | PP: 541-547 | Volume-8 Issue-12, October 2019. | Retrieval Number: L34221081219/2019©BEIESP | DOI: 10.35940/ijitee.L3422.1081219
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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: In the present evolving technology, an Automated Optical Inspection is a solution for identifying the various types of defects occurring in assembled PCB with SMT components. As these high-end machines are expensive, moreover the small scale industries can’t afford such a huge investment, in this paper a low cost image processing technique where a good known reference image is compared with the acquired image is being tried. This work provides an automated approach for identifying few of the defects related to the SMT components found in the assembled PCB, using three different techniques namely Contour Analysis, Optical Character Recognition and Pixel Subtraction for identifying shifted components, value of the components and missing components respectively in LabVIEW platform. The time taken for identifying the various defects through different techniques are calculated and tabulated. Using these techniques the number of errors can be decreased in turn the end performance can also be enhanced with the increased production yield.
Keywords: Assembled Printed Circuit Board (PCBA), Automated Optical Inspection (AOI), Optical Character Recognition (OCR), Surface Mount Technology (SMT).
Scope of the Article: Pattern Recognition