Date of Award
12-2004
Degree Name
Master of Science in Engineering
Department
Electrical and Computer Engineering
First Advisor
Dr. Ikhlas Abdul-Qader
Second Advisor
Dr. R. Gejji
Third Advisor
Dr. Osama Abudayyeh
Fourth Advisor
Dr. M. Niewiadomska-Bugaj
Access Setting
Masters Thesis-Open Access
Abstract
An algorithm to extract features from digital images such as cracks in concrete bridges for automated inspection is developed. The algorithm is based on the use of Principal Component Analysis (PCA). In general, PCA is used to reduce the dimensionality of a data set that consists of a large number of interrelated variables while retaining the variation present in the original data set. This ability of PCA will be used in this project to identify clusters using two training sets of images. Linear structure modeling is used to emphasize the image features (cracks) prior to applying PCA. Whole images processing and block processing are used with different distance measures to optimize the accuracy of the results. Real concrete bridge images with cracks. of different sizes and shapes as well as non-cracked images are used. The algorithm development and experimental results are presented.
Recommended Citation
Riaz Ahmed, Kawshif Muhammed, "Feature Detection using Linear Structure Modeling and PCA" (2004). Masters Theses. 4754.
https://scholarworks.wmich.edu/masters_theses/4754