Naïve Bayesian classifier for human shape recognition

  title={Na{\"i}ve Bayesian classifier for human shape recognition},
  author={Ahmad Rodzi Mahmud and N. Md Tahir},
  journal={2013 IEEE 9th International Colloquium on Signal Processing and its Applications},
The aim of this study is to investigate the potential of Radon Transform and Regularized Principal Component Analysis as feature extraction for classification of pedestrian, non-pedestrian and vehicles. Several classification techniques are evaluated and verified based on accuracy, specificity and computational time. Initial findings showed that the best classification technique is Naïve Bayesian along with Gaussian as kernel with 100% accuracy and execution time of 0.016s respectively for… CONTINUE READING
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