DocumentCode :
2772853
Title :
An Invariant Approach for Image Recognition
Author :
Zuniga-Segura, Erick ; Sánchez-Díaz, Guillermo
Author_Institution :
Center of Technol. Res. on Inf. & Syst., UAEH, Pachuca
Volume :
2
fYear :
2006
fDate :
Sept. 2006
Firstpage :
30
Lastpage :
34
Abstract :
Shape-of-object representation has always been an important topic in image processing and pattern recognition. This work deals with representation of shape of objects, and approaches to recognize objects. Several invariant techniques are widely used to represent an object because they preserve information and allow considerable data reduction. In this paper, a new approach based on a code representation and testor theory is presented. The proposed method is invariant under translation, scaling and rotation. Also, the paper discusses the capabilities of the method in recognizing objects. In addition, results using simple figures classes are show
Keywords :
computer vision; image recognition; image representation; object recognition; code representation; computer vision; image processing; image recognition; image tester theory; object recognition; pattern recognition; shape-of-object representation; Application software; Computer vision; Image processing; Image recognition; Image representation; Logic testing; Machine learning; Machine vision; Pattern recognition; Shape; Computer Vision; Invariants; logical combinatorial pattern recognition.; testors theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Robotics and Automotive Mechanics Conference, 2006
Conference_Location :
Cuernavaca
Print_ISBN :
0-7695-2569-5
Type :
conf
DOI :
10.1109/CERMA.2006.14
Filename :
4019766
Link To Document :
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