Title :
A recursive low level vision system
Author :
Guan, Ling ; Perry, Stuart ; Wong, Hausan
Author_Institution :
Dept. of Electr. Eng., Sydney Univ., NSW, Australia
Abstract :
The paper addresses a very important, yet one of the difficult issues in computer vision and visualization-low level vision modeling. It proposes a novel low level vision model which recursively integrates adaptive filtering, segmentation and edge detection. The model has strong biological merits: a) the model architecture is based on a biologically inspired neural network-network of networks which simulates human visual cortex; b) evolutionary computation is applied to identify the hierarchy and clusters in the network. But the model does not constrain itself by the biological facts. Instead, it proposes that by using clustering method, adaptive filtering, segmentation and edge detection are naturally linked to one another. The feasibility of the concept is demonstrated via a visual example
Keywords :
adaptive filters; computer vision; data visualisation; edge detection; image segmentation; adaptive filtering; biological merits; biologically inspired neural network; computer vision; edge detection; evolutionary computation; human visual cortex; image segmentation; recursive low level vision system; visualization; Adaptive filters; Biological system modeling; Brain modeling; Computational modeling; Computer architecture; Computer vision; Image edge detection; Machine vision; Neural networks; Visualization;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.625825