FACE DETECTION ON GRAYSCALE AND COLOR IMAGES USING COMBINED CASCADE OF CLASSIFIERS

Authors

  • Yuriy Kurylyak
  • Ihor Paliy
  • Anatoly Sachenko
  • Amine Chohra
  • Kurosh Madani

DOI:

https://doi.org/10.47839/ijc.8.1.657

Keywords:

Face Detection, Skin Color Segmentation, Haar-like Features’ Cascade of Weak Classifiers, Convolutional Neural Network, Combined Cascade of Classifiers.

Abstract

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.

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Published

2014-08-01

How to Cite

Kurylyak, Y., Paliy, I., Sachenko, A., Chohra, A., & Madani, K. (2014). FACE DETECTION ON GRAYSCALE AND COLOR IMAGES USING COMBINED CASCADE OF CLASSIFIERS. International Journal of Computing, 8(1), 61-71. https://doi.org/10.47839/ijc.8.1.657

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Articles