A scale-independent method for object recognition and visual positioning in nonoptimal conditions

Ilkka Moring, Hannu Hakalahti

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)

Abstract

Object recognition and visual positioning frequently involve major difficulties like variable illumination, low contrast, occlusions and shadows. Experience has shown that binary methods do not give consistent results in the factory. A gray-level method is reported for recognition and alignment that exploits local features of object contours in matching the model with the scene. The method allows for recognizing two-dimensional objects, which differ from the modeled object, in nonoptimal conditions. The strategy of the method is to accumulate local evidences of matches using a Hough-type procedure.
Original languageEnglish
Title of host publicationEighth International Conference on Pattern Recognition
PublisherIEEE Institute of Electrical and Electronic Engineers
Pages773-775
ISBN (Print)978-0-8186-8742-6
Publication statusPublished - 1986
MoE publication typeA4 Article in a conference publication
Event8th International Conference on Pattern Recognition - Paris, France
Duration: 28 Oct 198631 Oct 1986

Conference

Conference8th International Conference on Pattern Recognition
Country/TerritoryFrance
CityParis
Period28/10/8631/10/86

Fingerprint

Dive into the research topics of 'A scale-independent method for object recognition and visual positioning in nonoptimal conditions'. Together they form a unique fingerprint.

Cite this