Hierarchical Gaussian Scale-Space on Androgenic Hair Pattern Recognition
Abstract: Androgenic hair
pattern stated to be the new biometric trait since 2014. The research to
improve the performance of androgenic hair pattern recognition system has begun
to be developed due to the problems that occurred when other apparent biometric
trait such as face is hidden from sight. The recognition system was built with
hierarchical Gaussian scale-space using 4 octaves and 3 levels in each octave.
The system also implemented the equalization process to adjust image’s intensity
by using histogram equalization. We analyzed 400 images of androgenic hair in
the database that were analyzed using 2-fold and 10-fold cross validation and
Euclidean distance to classify it. The experimental results showed that our
proposed method gave better performance compared to previous work that used
Haar wavelet transformation and principal component analysis as the main
method. The best recognition precision was 94.23 % obtained from the base
octave with the third level using histogram equalization and 10-fold cross
validation.
Keywords: androgenic hair
pattern, biometric identification, hierarchical Gaussian scale-space, histogram
equalization, pattern recognition
Author: Regina Lionnie, Mudrik
Alaydrus
Journal Code: jptkomputergg170178
