作者
Muh Arif Rahman, I Ketut Edy Purnama, Mauridhi Hery Purnomo
发表日期
2014/8/19
研讨会论文
2014 International Conference on Intelligent Autonomous Agents, Networks and Systems
页码范围
58-61
出版商
IEEE
简介
Human skin detection is an important preliminary stage to improve the performance of other areas of object detection or recognition such as human face detection, hand gesture recognition, and pornography contents detection. Popular methods in this area are processing a single image pixel in HSV or YCbCr color spaces. The limitation of these approaches is they cannot address the wide range of the skin color distribution. This paper proposes a new approach by combining two model of skin color for each pixel into a vector contains color elements of H, S, Cb, and Cr. A set of experiments prove that the method produces an True Positif Rate (TPR) of 93.89% and False Positif Rate (FPR) of 10.75%. This result is significantly higher comparing those produced by single color models.
引用总数
2016201720182019202020212022202320242361034362
学术搜索中的文章
MA Rahman, IKE Purnama, MH Purnomo - … on Intelligent Autonomous Agents, Networks and …, 2014