Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Mechanical Engineering
Robust Fuzzyclustering For Object Recognition And Classification Of Relational Data, Sumit Sen
Robust Fuzzyclustering For Object Recognition And Classification Of Relational Data, Sumit Sen
Dissertations
Prototype based fuzzy clustering algorithms have unique ability to partition the data while detecting multiple clusters simultaneously. However since real data is often contaminated with noise, the clustering methods need to be made robust to be useful in practice. This dissertation focuses on robust detection of multiple clusters from noisy range images for object recognition. Dave's noise clustering (NC) method has been shown to make prototype-based fuzzy clustering techniques robust. In this work, NC is generalized and the new NC membership is shown to be a product of fuzzy c-means (FCM) membership and robust M-estimator weight (or possibilistic membership). Thus …
Robust Approach To Object Recognition Through Fuzzy Clustering And Hough Transform Based Methods, Tianxiong Fu
Robust Approach To Object Recognition Through Fuzzy Clustering And Hough Transform Based Methods, Tianxiong Fu
Dissertations
Object detection from two dimensional intensity images as well as three dimensional range images is considered. The emphasis is on the robust detection of shapes such as cylinders, spheres, cones, and planar surfaces, typically found in mechanical and manufacturing engineering applications. Based on the analyses of different HT methods, a novel method, called the Fast Randomized Hough Transform (FRHT) is proposed. The key idea of FRHT is to divide the original image into multiple regions and apply random sampling method to map data points in the image space into the parameter space or feature space, then obtain the parameters of …