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QUAD FLAT NO-LEAD (QFN) DEVICE FAULTY DETECTION USING GABOR WAVELETS

Tay , Wai Lun (2014) QUAD FLAT NO-LEAD (QFN) DEVICE FAULTY DETECTION USING GABOR WAVELETS. IRC, Universiti Teknologi PETRONAS. (Submitted)

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Abstract

Computer vision inspection system using image processing algorithms have been utilized by many manufacturing companies as a method of quality control. Since manufacturing industries comprise of many types of products, various image processing algorithms have been developed to suit different type of outputting products. In this paper, we explored Gabor wavelet feature extraction as a method for vision inspection. Unlike conventional vision inspection system which require manual human configuration of inspection algorithms, our experiment uses Gabor wavelets to fractionate the image into distinctive scales and orientations. Through chi-square distance computation, the physical quality of Quad Flan No-Lead (QFN) device can be distinguished by computing the dissimilarity of the test image with the trained database, thus eliminating the weakness of human errors in configuration of vision systems. We performed our algorithm testing using 64 real-world production images obtained from a 0.3 megapixel monochromatic industrial smart vision camera. The images consists a mixture of physically good and defected QFN units. The proposed algorithm achieved 98.46% accuracy rate with the average processing time of 0.457 seconds per image.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Engineering > Electrical and Electronic
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 24 Feb 2015 10:25
Last Modified: 25 Jan 2017 09:36
URI: http://utpedia.utp.edu.my/id/eprint/14737

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