| dc.creator | Lozano-Perez, Tomas | |
| dc.date | 2004-10-01T20:37:20Z | |
| dc.date | 2004-10-01T20:37:20Z | |
| dc.date | 1975-05-01 | |
| dc.date.accessioned | 2013-10-09T02:41:20Z | |
| dc.date.available | 2013-10-09T02:41:20Z | |
| dc.date.issued | 2013-10-09 | |
| dc.identifier | AIM-329 | |
| dc.identifier | http://hdl.handle.net/1721.1/5796 | |
| dc.identifier.uri | http://koha.mediu.edu.my:8181/xmlui/handle/1721 | |
| dc.description | Much low-level vision work in AI deals with one-dimensional intensity profiles. This paper describes PROPAR, a system that allows a convenient and uniform mechanism for recognizin such profiles. PROPAR is a modified Augmented Transition Networks parser. The grammar used by the parser serves to describe and label the set of acceptable profiles. The input to the parser are descriptions of segments of a piecewise linear approximation to an intensity profile. A sample grammar is presented and the results discussed. | |
| dc.format | 25 p. | |
| dc.format | 2058828 bytes | |
| dc.format | 1501433 bytes | |
| dc.format | application/postscript | |
| dc.format | application/pdf | |
| dc.language | en_US | |
| dc.relation | AIM-329 | |
| dc.title | Parsing Intensity Profiles |
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