A Machine Vision For Complex Industrial Parts With Learning Capability
Proceedings of the Fourth International Joint Conference on Artificial Intelligence. Robots And Productivity Technology. Pages 819--1.
Abstract
This paper describes a versatile machine vision system that can recognize a variety of complex industrial parts based on the previously learned models of them. It proposes a model guided approach for recognition in which models of objects direct recognition process by suggesting the features to be examined next and their predicted locations. For the system to be readily applied to new tasks, it can automatically generate the models of objects while a human operator showing example parts and teaching important features of them interactively on displays. The system has been applied to various sets of parts of small industrial gasoline engines and the result was satisfactory.
@inproceedings{ijcai1975p130,
title = {A Machine Vision For Complex Industrial Parts With Learning Capability},
author = {Yachida, Masahiko and Tsuji, Saburo},
booktitle = {Proceedings of the Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-75}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Patrick Winston and Carl Hewitt},
pages = {819---1},
year = {1975},
note = {Robots And Productivity Technology},
url = {https://ijcai.org/proceedings/1975/130},
}
TY - CPAPER TI - A Machine Vision For Complex Industrial Parts With Learning Capability AU - Yachida, Masahiko AU - Tsuji, Saburo T2 - Proceedings of the Fourth International Joint Conference on Artificial Intelligence, IJCAI-75 PB - International Joint Conferences on Artificial Intelligence PY - 1975 SP - 819 EP - -1 UR - https://ijcai.org/proceedings/1975/130 ER -Copied
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