DocumentCode
2030647
Title
A central distance method for invariant recognition of digital figures
Author
Kaneko, Teruyuki ; Sagara, Tetsuo ; Takeda, Takashi ; Takiyama, Ryuzo
Author_Institution
Dept. of Mech. Eng., Nagasaki Inst. of Appl. Sci., Japan
Volume
3
fYear
1999
fDate
1999
Firstpage
1208
Abstract
The authors have previously (1998, 1999) developed a description method for the recognition of non-singly connected figures using a “self-distance function” which allows for shift, scaling and rotational variation. The self-distance function is computed for all combinations of the points which make up the figures, so that the self-distance function can be calculated in O(n2) operations via an n-point figure, which is time-consuming. This paper proposes a “central distance function” to reduce the computation time. In this improved version, we measure the distances between the “centre of gravity” of the digital figure and the points making up the digital figure, so that the central distance function can be calculated in O(n) operations via an n-point digital figure. Experimental results show the usefulness of the proposed method
Keywords
computational complexity; distance measurement; image recognition; invariance; central distance function; computation time; computational complexity; digital figures; invariant recognition; nonsingly connected figures; rotational invariance; scale invariance; self-distance function; shift invariance; Frequency; Genetic mutations; Gravity;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Information Processing, 1999. Proceedings. ICONIP '99. 6th International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-5871-6
Type
conf
DOI
10.1109/ICONIP.1999.844711
Filename
844711
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