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The aim of this study is to investigate the potential of Radon Transform and Regularized Principal Component Analysis as feature extraction for classification of human and non human. Several training algorithms are used for the neural network. The finding of the investigation shows that the best training algorithm is Lavenberg-Marquardt (LM). In addition, the execution time taken by LM is fastest among the training.The outcomes of the proposed method using LM are 0% False Rejection Rate (FRR) and 0% False Acceptance Rate (FAR)ona database of 100 images on each category.
Published in:
Control and System Graduate Research Colloquium (ICSGRC), 2012 IEEE
Date of Conference: 16-17 July 2012
- Page(s):
- 298 - 302
- Print ISBN:
- 978-1-4673-2035-1
- INSPEC Accession Number:
- 12964177
- Conference Location :
- Shah Alam, Selangor
- Digital Object Identifier :
- 10.1109/ICSGRC.2012.6287180
- Product Type:
- Conference Publications
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