Inspection of printed circuit boards using data mining of image features
"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.
M.S. in Computer Science
University of Missouri--Rolla
xii, 152 leaves
© 2003 Swapna Ragini Ayyavari, All rights reserved.
Thesis - Citation
Library of Congress Subject Headings
Quality control -- Optical methods
Print OCLC #
Link to Catalog Record
Full-text not available: Request this publication directly from Missouri S&T Library or contact your local library.http://laurel.lso.missouri.edu/record=b5090024~S5
Ayyavari, Swapna Ragini, "Inspection of printed circuit boards using data mining of image features" (2003). Masters Theses. 2459.