Open AccessFACE DETECTION ON GRAYSCALE AND COLOR IMAGES USING COMBINED CASCADE OF CLASSIFIERS
Author(s) -
Yuriy Kurylyak,
Ihor Paliy,
А. В. Саченко,
Amine Chohra,
Kurosh Madani
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.8.1.657
Subject(s) - artificial intelligence , grayscale , computer science , face detection , computer vision , color space , cascade , false positive paradox , pattern recognition (psychology) , face (sociological concept) , segmentation , facial recognition system , pixel , image (mathematics) , social science , sociology , chemistry , chromatography
The paper describes improved face detection methods for grayscale and color images using the combined cascade of classifiers and skin color segmentation. The combined cascade with proposed face candidates’ verification method allows achieving one of the best detection rates on CMU test set and a high processing speed suitable for a video flow processing. It’s also shown that the mixture of color spaces is more efficient during the skin color segmentation than the application of one color space. A lot of experiments are made to choose rational parameters for the developed face detection system in order to improve the detection rate, false positives’ number and system’s speed.