DocumentCode :
2443962
Title :
Soft contaminant detection using neural networks: techniques and limitations
Author :
Patel, D. ; Hannah, I. ; Davies, E.R.
Author_Institution :
Dept. of Phys., R. Holloway & Bedford New Coll., Egham, UK
Volume :
7
fYear :
1994
fDate :
27 Jun-2 Jul 1994
Firstpage :
4316
Abstract :
We deal with the detection of contaminants in bags of frozen corn kernels. Foreign objects (FOs) buried in the bags are not visible to a conventional camera and consequently in order to view the contents of the bags we use X-ray imaging. The aim of this research is to develop a neural net based image analysis system which detects and segments any FOs that might be in the bags
Keywords :
X-ray imaging; automatic optical inspection; food processing industry; image segmentation; neural nets; object recognition; quality control; X-ray imaging; food processing industry; foreign object detection; frozen corn kernels; image analysis system; image segmentation; neural networks; object recognition; soft contaminant detection; Artificial neural networks; Glass; Image texture analysis; Impurities; Kernel; Neural networks; Plastics; X-ray detection; X-ray detectors; X-ray imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
Type :
conf
DOI :
10.1109/ICNN.1994.374961
Filename :
374961
Link To Document :
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