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首页> 外文期刊>Electronic Letters on Computer Vision and Image Analysis: ELCVIA >Efficient Iris and Eyelids Detection from Facial Sketch Images
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Efficient Iris and Eyelids Detection from Facial Sketch Images

机译:从面部素描图像中有效检测虹膜和眼睑

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摘要

In this paper, we propose a simple yet effective technique for an automatic iris and eyelids detection method for facial sketch images. Our system uses Circular Hough Transformation (CHT) algorithm for iris localization process and a low level grayscale analysis for eyelids contour segmentation procedure. We limit the input face for the system to facial sketch photos with frontal pose, illumination invariant, neutral expression and without occlusions. CUHK and IIIT-D sketch databases are used to acquire the experimental results. As to validate the proposed algorithm, experiments on ground truth for iris and eyelids segmentation, which are prepared at our lab, is conducted. The iris segmentation from the proposed method gives the best accuracy of 92.93 and 86.71 based on F-measure evaluation for IIIT-D and CUHK, respectively. For eyelids segmentation, on the other hand, the proposed algorithm achieves an average of 4 standard deviation which indicates the closeness of proposed method to ground truth.
机译:在本文中,我们提出了一种简单而有效的技术,用于面部素描图像的自动虹膜和眼睑检测方法。我们的系统使用圆形霍夫变换(CHT)算法进行虹膜定位过程,并使用低级灰度分析进行眼睑轮廓分割过程。我们将系统的输入脸部限制为正面姿势,照度不变,中性表情且没有遮挡的面部素描照片。中大和IIIT-D草图数据库用于获得实验结果。为了验证该算法的有效性,我们在实验室中进行了虹膜和眼睑分割的地面真实性实验。基于F测度分别对IIIT-D和CUHK进行虹膜分割,其虹膜分割的最佳准确度为92.93和86.71。另一方面,对于眼睑分割,所提出的算法获得4个标准差的平均值,这表明所提出的方法与地面真相的接近度。

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