Computer Engineering and Applications ›› 2015, Vol. 51 ›› Issue (12): 161-164.

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Eye detection based on improved gray-level integration projection in polar coordinates

XIU Chunbo1,2, LU Shaolei1,2   

  1. 1.Key Laboratory of Advanced Electrical Engineering and Energy Technology, Tianjin Polytechnic University, Tianjin 300387, China
    2.School of Electrical Engineering and Automation, Tianjin Polytechnic University, Tianjin 300387, China
  • Online:2015-06-15 Published:2015-06-30



  1. 1.天津工业大学 电工电能新技术天津市重点实验室,天津 300387
    2.天津工业大学 电气工程与自动化学院,天津 300387

Abstract: Conventional gray-level integration projection can not detect the eyes in the rotating face image. In order to overcome this shortcoming, an improved gray-level integration projection method in the polar coordinates is proposed. Face regions are extracted from the image by the feature of skin color. Gray-level integration is projected to the polar angle in the face region to detect the angles of eyes. Pixels in the direction of eyes are projected to the horizontal direction to determine the position of eyes. The method can detect eyes from several different posture faces in the same image. A lot of simulation results show that the detection performance of the method has good robustness to the rotational variation of face. Thus, the method can expand the eye detection application of gray-level integration projection method.

Key words: eye detection, polar coordinates, gray-level integration projection, rotation

摘要: 为了克服传统灰度积分投影方法无法有效定位旋转人脸图像中人眼的缺点,提出了一种基于极坐标系的灰度积分投影方法。利用肤色特征对给定图像进行人脸区域的确定,在人脸区域内按极角方向进行灰度积分投影,确定出人眼所在角度,将人眼角度方向的像素灰度值做水平方向积分投影,从而确定出人眼的位置。该方法能够实现同一幅图像中多个不同姿态人脸的人眼定位。大量的仿真实验表明,该方法的识别性能对人脸的旋转变化具有良好的鲁棒性,能够提高灰度积分投影方法对人眼定位的适用范围。

关键词: 人眼定位, 极坐标, 灰度积分投影, 旋转