Die defect classification using image processing

This work presents die defect classification using image processing. The detection of the flaw is based on the defect features in the die. Each unique defect or feature structure is defined from samples that has been collected by Visual Inspection Inspectors. The defects are then grouped into user d...

Full description

Saved in:
Bibliographic Details
Main Author: Maniam, Darmadevaindra
Format: Thesis
Language:English
Published: 2015
Subjects:
Online Access:http://eprints.utm.my/id/eprint/53921/1/DarmadevaindraManiamMFKE2015.pdf
http://eprints.utm.my/id/eprint/53921/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:85629
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknologi Malaysia
Language: English
Description
Summary:This work presents die defect classification using image processing. The detection of the flaw is based on the defect features in the die. Each unique defect or feature structure is defined from samples that has been collected by Visual Inspection Inspectors. The defects are then grouped into user definition categories such as blob, pin hole, underfill and die crack.This work also describes the image processing algorithms utilized to perform defect classification. The defect classification was developed from MATLAB program.It is aimed at locating the Region of Interest of the die from the image and extract it. The extracted image is then used to classify or recognize the specific classification category of the defect.Total samples that is being used in this project is 67 die samples. The results obtained from this work shows the overall accuracy of 94% for die defect detection and 87% for defect classification.