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

Ilkka Moring; Hannu Hakalahti

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

Ilkka Moring
, Hannu Hakalahti

VTT Technical Research Centre of Finland

VTT (former employee or external)

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-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 language	English
Title of host publication	Eighth International Conference on Pattern Recognition
Publisher	IEEE Institute of Electrical and Electronic Engineers
Pages	773-775
ISBN (Print)	978-0-8186-8742-6
Publication status	Published - 1986
MoE publication type	A4 Article in a conference publication
Event	8th International Conference on Pattern Recognition - Paris, France Duration: 28 Oct 1986 → 31 Oct 1986

Conference

Conference	8th International Conference on Pattern Recognition
Country/Territory	France
City	Paris
Period	28/10/86 → 31/10/86

Cite this

@inproceedings{5516d07a3c9342c99fdcffb5abfa0559,

title = "A scale-independent method for object recognition and visual positioning in nonoptimal conditions",

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.",

author = "Ilkka Moring and Hannu Hakalahti",

year = "1986",

language = "English",

isbn = "978-0-8186-8742-6",

pages = "773--775",

booktitle = "Eighth International Conference on Pattern Recognition",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

address = "United States",

note = "8th International Conference on Pattern Recognition ; Conference date: 28-10-1986 Through 31-10-1986",

}

A scale-independent method for object recognition and visual positioning in nonoptimal conditions. / Moring, Ilkka; Hakalahti, Hannu.
Eighth International Conference on Pattern Recognition. IEEE Institute of Electrical and Electronic Engineers, 1986. p. 773-775.

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

TY - GEN

T1 - A scale-independent method for object recognition and visual positioning in nonoptimal conditions

AU - Moring, Ilkka

AU - Hakalahti, Hannu

PY - 1986

Y1 - 1986

N2 - 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.

AB - 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.

M3 - Conference article in proceedings

SN - 978-0-8186-8742-6

SP - 773

EP - 775

BT - Eighth International Conference on Pattern Recognition

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 8th International Conference on Pattern Recognition

Y2 - 28 October 1986 through 31 October 1986

ER -

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

Abstract

Conference

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