Earticle

초록

영어

Skin region detection in images is an important process in many computer vision applications targeting humans such as hand gesture recognition and face identification. It usually starts at a pixel-level, and involves a pre-process of color spae transformation followed by a classification process. A color space transformation is assumed to increase separability between skin classes and other classes, to increase similarity among different skin tones, and to bring a robust performance under varying imaging conditions, without any complicated analysis. In this paper, we examine if the color space transformation actually brings those benefits to the problem of skin region detection on a set of human hand images with different postures, backgrounds, people, and illuminations. Our experimental results indicate that color space transfomation affects the skin detection performance. Although the performance depends on camera and surround conditions, normalized [R, G, B] color space may be a good choice in general.

목차

Abstract
 1 Introduction
 2 Color space transformations
 3 Experiements
  3.1 Datasets and cameras used
  3.2 Pixels classified for hand regions and non-hand regions
  3.3 Color space transformation and hand region detection efficiency
 4 ConcIusions
 References

키워드

저자

• Kim, Jun-Yup [ Computer and Communication Engineering Department, Daegu University ]
• Do, Yong-Tae [ Electronic Engineering Department, Daegu University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국정보기술응용학회 학술대회

• 간기

  부정기

• 수록기간

  2001~2011

• 십진분류

  KDC 005 DDC 005