Automated Switching System for Skin Pixel Segmentation in Varied Lighting

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📝 Original Info

  • Title: Automated Switching System for Skin Pixel Segmentation in Varied Lighting
  • ArXiv ID: 1304.4711
  • Date: 2013-04-18
  • Authors: Researchers from original ArXiv paper

📝 Abstract

In Computer Vision, colour-based spatial techniquesoften assume a static skin colour model. However, skin colour perceived by a camera can change when lighting changes. In common real environment multiple light sources impinge on the skin. Moreover, detection techniques may vary when the image under study is taken under different lighting condition than the one that was earlier under consideration. Therefore, for robust skin pixel detection, a dynamic skin colour model that can cope with the changes must be employed. This paper shows that skin pixel detection in a digital colour image can be significantly improved by employing automated colour space switching methods. In the root of the switching technique which is employed in this study, lies the statistical mean of value of the skin pixels in the image which in turn has been derived from the Value, measures as a third component of the HSV. The study is based on experimentations on a set of images where capture time conditions varying from highly illuminated to almost dark.

💡 Deep Analysis

Deep Dive into Automated Switching System for Skin Pixel Segmentation in Varied Lighting.

In Computer Vision, colour-based spatial techniquesoften assume a static skin colour model. However, skin colour perceived by a camera can change when lighting changes. In common real environment multiple light sources impinge on the skin. Moreover, detection techniques may vary when the image under study is taken under different lighting condition than the one that was earlier under consideration. Therefore, for robust skin pixel detection, a dynamic skin colour model that can cope with the changes must be employed. This paper shows that skin pixel detection in a digital colour image can be significantly improved by employing automated colour space switching methods. In the root of the switching technique which is employed in this study, lies the statistical mean of value of the skin pixels in the image which in turn has been derived from the Value, measures as a third component of the HSV. The study is based on experimentations on a set of images where capture time conditions varying

📄 Full Content

In Computer Vision, colour-based spatial techniquesoften assume a static skin colour model. However, skin colour perceived by a camera can change when lighting changes. In common real environment multiple light sources impinge on the skin. Moreover, detection techniques may vary when the image under study is taken under different lighting condition than the one that was earlier under consideration. Therefore, for robust skin pixel detection, a dynamic skin colour model that can cope with the changes must be employed. This paper shows that skin pixel detection in a digital colour image can be significantly improved by employing automated colour space switching methods. In the root of the switching technique which is employed in this study, lies the statistical mean of value of the skin pixels in the image which in turn has been derived from the Value, measures as a third component of the HSV. The study is based on experimentations on a set of images where capture time conditions varying from highly illuminated to almost dark.

Reference

This content is AI-processed based on ArXiv data.

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