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
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;
Conference_Titel :
Intelligent Control, 1996., Proceedings of the 1996 IEEE International Symposium on
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-2978-3
DOI :
10.1109/ISIC.1996.556202