• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.233-238
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• 2005

With iris recognition algorithm, unique iris code can be generated and user can be identified by using iris pattern. However, if unnecessary information such as eyelash is included in iris region, the error for iris recognition is increased, consequently. In detail, if iris region is used to generate ins code not excluding eyelash and the position of eyelash is moved, the iris codes are also changed and the error rate is increased. To overcome such problem, we propose the method of detecting eyelash by using mask and excluding the detected eyelash region in case of generating iris code. Experimental results show that EER(Equal Error Rate) for iris recognition using the proposed algorithm is lessened as much as $0.18\%$ compared to that not using it.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.898-905
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• 2005

Iris recognition Is that identifies a user based on the unique iris muscle patterns which has the functionalities of dilating or contracting pupil region. Because it is reported that iris recognition is more accurate than other biometries such as face, fingerprint, vein and speaker recognition, iris recognition is widely used in the high security application domain. However, if unnecessary information such as eyelid and eyelash is included in iris region, the error for iris recognition is increased, consequently. In detail, if iris region is used to generate iris code including eyelash and eyelid, the iris codes are also changed and the error rate is increased. To overcome such problem, we propose the method of detecting eyelid by using pyramid searching parabolic deformable template. In addition, we detect the eyelash by using the eyelash mask. Experimental results show that EER(Equal Error Rate) for iris recognition using the proposed algorithm is lessened as much as $0.3\%$ compared to that not using it.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.181-183
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• 2004

In this paper, We proposed an algorithm which extraction iris region from 2D image. Our method is composed of three parts : internal boundary defection and external boundary detection. Since eyelid and eyelash cover part of the boundary and the size of iris changes continuously, it is difficult to extract iris region accurately. For the interior and exterior boundary detection, we used partial differentiation of histogram. Performance of the proposed algorithm is tested and evaluated using 360 iris image samples.

• ETRI Journal
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• v.34 no.4
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• pp.542-552
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• 2012

In this paper, a gaze estimation method is proposed for use with a large-sized display at a distance. Our research has the following four novelties: this is the first study on gaze-tracking for large-sized displays and large Z (viewing) distances; our gaze-tracking accuracy is not affected by head movements since the proposed method tracks the head by using a near infrared camera and an infrared light-emitting diode; the threshold for local binarization of the pupil area is adaptively determined by using a p-tile method based on circular edge detection irrespective of the eyelid or eyelash shadows; and accurate gaze position is calculated by using two support vector regressions without complicated calibrations for the camera, display, and user's eyes, in which the gaze positions and head movements are used as feature values. The root mean square error of gaze detection is calculated as $0.79^{\circ}$ for a 30-inch screen.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2231-2238
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• 2011

In this paper, the extract method of eye and eye-line from picture of a person is proposed. Most of existing papers are to extract the position of eyeball but in this paper, by extracting not only the position of eyeball but also eye-line, it can be applied to the face application program variously. The experimental data of the input picture is a full face photograph taken by smart phone, basically the picture is limited to the face of one person and back ground can be taken from every where and no restriction of race. The proposed method is to extract face candidated area by using Harr Classifier and set up the candidate area of eye position from face candidate area. To extract high value from eye candidate area using dilate operation, and proposed the method to classify eye and eyelash by local thresholding of the picture. After that, using thresholding image from eyemapC that Hsu's suggested, and separated the area with eye and without eye. Finally extract the contour of eye and detect eye-line using optimum ellipse estimation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.94-104
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• 2007

Iris recognition is biometric technology which uses a unique iris pattern of user in order to identify person. In the captured iris image by conventional iris recognition camera, it is often the case with eyelid occlusion, which covers iris information. The eyelids are unnecessary information that causes bad recognition performance, so this paper proposes robust algorithm in order to detect eyelid. This research has following three advantages compared to previous works. First, we remove the detected eyelash and specular reflection by linear interpolation method because they act as noise factors when locating eyelid. Second, we detect the candidate points of eyelid by using mask in limited eyelid searching area, which is determined by searching the cross position of eyelid and the outer boundary of iris. And our proposed algorithm detects eyelid by using parabolic hough transform based on the detected candidate points. Third, there have been many researches to detect eyelid, but they did not consider the rotation of eyelid in an iris image. Whereas, we consider the rotation factor in parabolic hough transform to overcome such problem. We tested our algorithm with CASIA Database. As the experimental results, the detection accuracy were 90.82% and 96.47% in case of detecting upper and lower eyelid, respectively.