Date of Award
Master of Science in Engineering
Electrical and Computer Engineering
Dr. Ikhlas Abdul-Qader
Dr. R. Gejji
Dr. Osama Abudayyeh
Dr. M. Niewiadomska-Bugaj
Masters Thesis-Open Access
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.
Riaz Ahmed, Kawshif Muhammed, "Feature Detection using Linear Structure Modeling and PCA" (2004). Master's Theses. 4754.