Perbandingan Pengenalan Citra Wajah Berbasis Reduksi Dimensionalitas Dengan Principal Component Analysis (PCA) dan Jaringan Saraf Tiruan

Budiman Budiman, Didit Dwi Permadi, Muhammad Khoirul Anam, Pradipta Ramadhinara

Abstract


This paper will describes human face recognition process using principal component analysis compared to artificial intelligence network approach. The basic idea for this research is dimensionality reduction of the image used for the recognition system. Principal component analysis reduce the dimensionality of image recognize using its eigen vector nd eigen value.  Dimensionality reduction used for Artificial Neural Network based on image processing technique. This research suggest new idea for using canny filter (edge detector) for dimensionality reduction. Artificial Neural Network used in this experiment based on backpropagation training. Experiment result  for these two approachs will be compared to recognize its performances.


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References


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