@inproceedings{3e29b1d0215041f08eec01c030e12ebb,
title = "3-D manufacturing feature recognition using super relation graph method",
abstract = "Recognizing machining features such as slots, holes and pockets is one of the major tasks of CAD/CAM. This research proposes the super relation graph (SRG) method which uses artificial intelligence, pattern recognition, artificial neural networks and computational geometry techniques for extracting shape features. The nodes of the SRG represent the faces in depressions; the links represent either super-concavity or face-to-face relationships which are generated from a set of new definitions of relationships between two faces. SRG feature representation scheme carries more information than previous models and the results obtained are proved to be better than the ones generated from most of the prominent existing methods.",
author = "Kao, \{Ching Yao\} and Kumara, \{Soundar R.T.\}",
year = "1993",
language = "English (US)",
isbn = "0898061326",
series = "Proceedings of the Industrial Engineering Research Conference",
publisher = "Publ by IIE",
pages = "614--618",
editor = "Mitta, \{Deborah A.\} and Burke, \{Laura I.\} and English, \{John R.\} and Jennie Gallimore and Georgia-Ann Klutke and Tonkay, \{Gregory L.\}",
booktitle = "Proceedings of the Industrial Engineering Research Conference",
note = "Proceedings of the 2nd Industrial Engineering Research Conference ; Conference date: 26-05-1993 Through 28-05-1993",
}