Masters Theses
Inspection of printed circuit boards using data mining of image features
Abstract
"This thesis focuses on an idea to inspect the defects on a bare PCB and to build a model, which identifies the board type as defective or non-defective and to identify the kind of defect with respect to hole and line, which are the features that define the PCB. The model is based on the Data Mining concepts and different data mining techniques such as Rough sets, Quinlan's C45, Neural networks, ART2 and K-means clustering.--Abstract, page iii.
Department(s)
Computer Science
Degree Name
M.S. in Computer Science
Publisher
University of Missouri--Rolla
Publication Date
Fall 2003
Pagination
xii, 152 pages
Note about bibliography
Includes bibliographical references.
Rights
© 2003 Swapna Ragini Ayyavari, All rights reserved.
Document Type
Thesis - Citation
File Type
text
Language
English
Subject Headings
Data miningQuality control -- Optical methodsPrinted circuits
Thesis Number
T 8415
Print OCLC #
55480944
Recommended Citation
Ayyavari, Swapna Ragini, "Inspection of printed circuit boards using data mining of image features" (2003). Masters Theses. 2459.
https://scholarsmine.mst.edu/masters_theses/2459
Share My Thesis If you are the author of this work and would like to grant permission to make it openly accessible to all, please click the button above.
