DocumentCode :
2345689
Title :
Multi-view invariant shape recognition based on neural networks
Author :
Yawichai, Kritsana ; Kitjaidure, Yuttana
Author_Institution :
Dept. of Electron., King Mongkut´´s Inst. of Technol. Ladkrabang, Bangkok
fYear :
2008
fDate :
3-5 June 2008
Firstpage :
1538
Lastpage :
1542
Abstract :
Several shape recognition systems based on pairwise shape matching technique have achieved high accuracy but they face a problem of time consumption when they are evaluated on a large database. So this drawback makes the system impractical for real-time applications. Motivated by this obstacle, we have investigated a novel and robust neural network solution to achieve high speed of shape recognition without sacrificing accuracy via the non-absolute 1-D triangle area representation (NATA). Our method has been evaluated over a number of affine distorted shapes. The experimental results demonstrate that a shape recognition system using the neural network can achieve high speed and accuracy comparable with the prior system.
Keywords :
image matching; neural nets; object recognition; multiview invariant shape recognition; neural network; pairwise shape matching technique; Data engineering; Databases; Face recognition; Gaussian noise; Image segmentation; Neural networks; Noise shaping; Real time systems; Robustness; Shape measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics and Applications, 2008. ICIEA 2008. 3rd IEEE Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1717-9
Electronic_ISBN :
978-1-4244-1718-6
Type :
conf
DOI :
10.1109/ICIEA.2008.4582776
Filename :
4582776
Link To Document :
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