MATEC Web of Conferences
Volume 61, 2016The International Seminar on Applied Physics, Optoelectronics and Photonics (APOP 2016)
|Number of page(s)||4|
|Section||Chapter 4 Information Technology|
|Published online||28 June 2016|
Research on Identification of Dust Particles on COF
School of Mechanical and Electric Engineering, Soochow University, 215021 Su Zhou, China
a Corresponding author: firstname.lastname@example.org
Chip On Film(COF) is the key component of electronic products, and is different from Printed Circuit Board(PCB). The properties of high flexibility, thin thickness, lightweight and high wiring density make it difficult to inspect COF, especially dust particles interference. Dust particles are similar to defects, and it is hard to identify dust particles from defects, so dust particles interference of quality test is the difficulty of automatic surface defect detection. In this paper, a new method to identify dust particles is discussed from abnormal area called junction points detection and machine learning method Support Vector Machine(SVM) according to the characteristics of dust particles. As a result, a 94.8% correct rate of dust particles images identification has been achieved with the method.
Key words: COF / Dust / Identification / Junction Point / SVM
© Owned by the authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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