Perbandingan DTCWT dan NMF pada Face Recognition menggunakan Euclidean Distance
DOI:
https://doi.org/10.21512/comtech.v5i1.2580Keywords:
Dual Tree Complex Wavelet transform (DT-CWT), Non-negative Matrix Factorization (NMF), face recognition, euclidean distanceAbstract
Dual tree complex wavelet transform (DTCWT) is widely used for representation of face image features. DTCWT is more frequently used than Gabor or Discrete Wavelet Transform (DWT) because it provides good directional selectivity in six different directions. Meanwhile, non-negative matrix factorization (NMF) is also frequently used since it can reduce high dimensional feature into smaller one without losing important features. This research focused on comparison between DTCWT and NMF as feature extraction and Euclidean Distance for classification. This research used ORL Faces database. Experimental result showed that NMF provided better results than DTCWT did. NMF reached 92% of accuracy and DTCWT reached 78% of accuracy.Plum Analytics
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