Title :
A neural network based histogramic procedure for fast image segmentation
Author :
Kothari, Ravi ; Klinkhachorn, Powsiri ; Huber, Henry A.
Author_Institution :
West Virginia Univ., Morgantown, WV, USA
Abstract :
The determination of the dimension of a lumber board, the location and extent of surface defects on it, are essential in the construction of a visual inspection station for the lumber industry. The paper presents a neural network based histogramic procedure that performs on the image of a board and can be used to determine the board dimension, the location and extent of surface defects on it, in near real time. The method is based on segmentation of the image based on multiple threshold information derived from a multi-layered neural network. Such a scheme can be applied in general to image analysis and the implementation shows fast processing requiring very little control over the environment. The construction of the network and its training are also discussed
Keywords :
computerised pattern recognition; computerised picture processing; inspection; neural nets; word processing; computerised pattern recognition; computerised picture processing; fast image segmentation; image analysis; lumber board; multi-layered neural network; neural network based histogramic procedure; surface defects; training; visual inspection station; word processing; Cameras; Colored noise; Image segmentation; Laser beam cutting; Machine vision; Neural networks; Noise generators; Pixel; Wood industry; Working environment noise;
Conference_Titel :
System Theory, 1991. Proceedings., Twenty-Third Southeastern Symposium on
Conference_Location :
Columbia, SC
Print_ISBN :
0-8186-2190-7
DOI :
10.1109/SSST.1991.138548
