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An Iris Detection Method Using the Hough Transform and Its Evaluation for Facial and Eye Movement

机译:基于霍夫变换的虹膜检测方法及其对面部和眼睛运动的评估

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Our research aims at applying information with regard to a user's gaze to computer interaction. In this paper, we propose an iris detection method that is adaptable to various face and eye movements taken from a facial image. First, our method determines the standard skin color from previous frame. The face region is determined using the color difference from the standard skin color. Secondly, the eye and mouth regions are extracted from the face region by hybrid template matching, which consists of edge and color features. Using our method, facial parts can be extracted against individual variation of faces and head movements. Finally, the iris regions are detected by using saturation and brightness from the extracted eye regions. Then, the iris positions are detected by the Hough transform. We evaluated our method using facial images containing various positions of faces and eyes. Our method achieved an accuracy rate of approximately 96% for eye region detection, and approximately 92% for iris detection.
机译:我们的研究旨在将有关用户凝视的信息应用于计算机交互。在本文中,我们提出了一种虹膜检测方法,该方法适用于从面部图像获取的各种面部和眼睛运动。首先,我们的方法根据前一帧确定标准肤色。使用与标准肤色之间的色差确定面部区域。其次,通过混合模板匹配从脸部区域提取眼睛和嘴部区域,该模板由边缘和颜色特征组成。使用我们的方法,可以针对面部和头部运动的个体变化提取面部部位。最终,通过使用来自提取的眼睛区域的饱和度和亮度来检测虹膜区域。然后,通过霍夫变换来检测虹膜位置。我们使用包含面部和眼睛不同位置的面部图像评估了我们的方法。我们的方法在眼睛区域检测中达到约96%的准确率,在虹膜检测中达到约92%的准确率。

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