Efficient Iris and eyelids detection from facial sketch images
T Boonchuan, S Setumin, A Radman… - ELCVIA: electronic letters …, 2018 - ddd.uab.cat
ELCVIA: electronic letters on computer vision and image analysis, 2018•ddd.uab.cat
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 …
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 …
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.
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