Open AccessFace recognition in four types of colour space: a performance analysis
Author(s) -
Hanung Adi Nugroho,
Rezqy Dwikara Goratama,
Eka Legya Frannita
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1088/1/012010
Subject(s) - ycbcr , artificial intelligence , face (sociological concept) , computer science , thresholding , color space , computer vision , face detection , pattern recognition (psychology) , segmentation , reliability (semiconductor) , facial recognition system , texture (cosmology) , image processing , color image , image (mathematics) , physics , quantum mechanics , social science , power (physics) , sociology
Face detection is one of the problems in computer vision with a large number of researches works. This research work aims to analyses the effect of performing various color spaces in face detection. 1100 images provided by SFA dataset was used in this study. The proposed method was initiated by pre-processing step. Then, segmentation step by using thresholding and morphological operation was conducted. For selecting face area, some features such as eccentricity, area and texture features were used. Finally, for validating the reliability of the proposed method, UTKface dataset was applied. This study obtained more than 90% accuracy of face detection in each color space. Moreover, the highest accuracy was obtained in YCbCr color space with 96.13%. This result was also strengthened with other experiment by using UTKface dataset. This experiment achieves accuracy of 80%. According to the performance analysis, the proposed method is reliable for recognizing face characteristic.