Date of Award
1-1-2004
Thesis Type
undergraduates
Document Type
Thesis
Divisions
fsktm
Department
Faculty of Computer Science & Information Technology
Institution
University of Malaya
Abstract
The pulse-coupled neuron, which is significantly-different from the conventional artificial neuron, is a result of recent research conducted on the visual cortex of cats and monkeys. Pulse-coupled neural networks (PCNNs) are modeled to capture the essence of recent understanding of image interpretation processes in biological neural systems. Study indicates that the PCNN is capable of image smoothing, image segmentation and feature extraction. The PCNN reduces noise in digital images better than traditional smoothing techniques. As an image segmented the PCNN performs well even when the intensity varies significantly within regions, and adjacent regions have overlapping intensity ranges.
Note
Academic Exercise (Bachelor’s Degree) – Faculty of Computer Science & Information Technology, University of Malaya, 2003/2004.
Recommended Citation
Siti Shufinaz, Mohd Zainudin, "Magnetic resonance image segmentation using pulse-coupled neural network / Siti Shufinaz Mohd Zainudin" (2004). Student Works (2000-2009). 2307.
https://knova.um.edu.my/student_works_2000s/2307