Facial space detection and eyes surrounded object detective technique on color image YCbCr and HSV
Suppakitti Sopasoap, Jakkree Srinonchat · 2017
The face detection has recently become an important aspect in biometric identification systems. Among many other facial features like position of nose, lips, eye, face contour acts as an important classifier in face detection. The same human's face can be different characteristics, if there are any objects on their face, such as, glasses. This can make an error on the recognition system. This article presents facial space detection and eyes surrounded object detective technique on color image YCbCr and HSV. The experiments have been tested in two environments; firstly the image with non-pattern background and finally the image with pattern background. The results show that the image with non-pattern background the system can detect face position for 96% and the eyes covered object position for 91% while the image with pattern background, the system can detected the face position for 86% and the eyes covered object position for 82%. This technique aims to develop and increase the effectiveness of face detection and eyes surrounded object detective technique.