DocumentCode
1896425
Title
Machine vision fuzzy object recognition and inspection using a new fuzzy neural network
Author
Chen, B. ; Hoberock, L.L.
Author_Institution
Sch. of Mech. & Aerosp. Eng., Oklahoma State Univ., Stillwater, OK, USA
fYear
1996
fDate
15-18 Sep 1996
Firstpage
206
Lastpage
211
Abstract
A new fuzzy neural network, termed FUZAMP, has been used to deal with situations where the available training data from a machine vision system includes uncertainty. It performs well when used to recognize different types of fuzzy objects presented at different locations and orientations in the camera field of view. FUZAMP has been implemented to correlate human evaluations with machine evaluations of the cleanliness of dishes. Results are compared to those obtained using the so-called fuzzy ARTMAP neural network, with FUZAMP achieving better accuracy than the fuzzy ARTMAP using the same training exemplars
Keywords
computer vision; fuzzy neural nets; inspection; object recognition; FUZAMP; cleanliness; fuzzy ARTMAP neural network; fuzzy neural network; inspection using; machine vision fuzzy object recognition; training data; Cameras; Fuzzy logic; Fuzzy neural networks; Fuzzy sets; Humans; Inspection; Machine vision; Neural networks; Sorting; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 1996., Proceedings of the 1996 IEEE International Symposium on
Conference_Location
Dearborn, MI
ISSN
2158-9860
Print_ISBN
0-7803-2978-3
Type
conf
DOI
10.1109/ISIC.1996.556202
Filename
556202
Link To Document