• Animal Bioscience
• /
• v.36 no.6
• /
• pp.980-989
• /
• 2023

Objective: Iris pattern recognition system is well developed and practiced in human, however, there is a scarcity of information on application of iris recognition system in animals at the field conditions where the major challenge is to capture a high-quality iris image from a constantly moving non-cooperative animal even when restrained properly. The aim of the study was to validate and identify Black Bengal goat biometrically to improve animal management in its traceability system. Methods: Forty-nine healthy, disease free, 3 months±6 days old female Black Bengal goats were randomly selected at the farmer's field. Eye images were captured from the left eye of an individual goat at 3, 6, 9, and 12 months of age using a specialized camera made for human iris scanning. iGoat software was used for matching the same individual goats at 3, 6, 9, and 12 months of ages. Resnet152V2 deep learning algorithm was further applied on same image sets to predict matching percentages using only captured eye images without extracting their iris features. Results: The matching threshold computed within and between goats was 55%. The accuracies of template matching of goats at 3, 6, 9, and 12 months of ages were recorded as 81.63%, 90.24%, 44.44%, and 16.66%, respectively. As the accuracies of matching the goats at 9 and 12 months of ages were low and below the minimum threshold matching percentage, this process of iris pattern matching was not acceptable. The validation accuracies of resnet152V2 deep learning model were found 82.49%, 92.68%, 77.17%, and 87.76% for identification of goat at 3, 6, 9, and 12 months of ages, respectively after training the model. Conclusion: This study strongly supported that deep learning method using eye images could be used as a signature for biometric identification of an individual goat.

• Information Systems Review
• /
• v.7 no.2
• /
• pp.1-21
• /
• 2005

Integrated Railroad Information System(IRIS) Construction Project is one of the super projects in Korea required to invest over 100 billion won and 10,000 engaged manpower until Dec 30, 2004. Composition of this paper is as follows; firstly, examined individual contents and aspects of IRIS, and studied formality and contents that have been based to project methodology for successful propulsion of project in overall situation of SI project progress until present. Secondly, presented for construction background of IRIS as well as Project Management and Project Development Methodologies. Thirdly, described each characteristic and development substance for individual systems after present whole contents and system image of the system. Finally, presented successful propulsion result of this project and development directions. We presented development example laying stress on IRIS's Project contents and propulsion circumstances. Evaluation about operation results should be analyzed and studied in detail operating system from now on.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.1 s.39
• /
• pp.19-25
• /
• 2006

Iris recognition is a bio metric personal identification which uses iris pattern of the pupil, and it is recognized as one of the best technology in personal identification and information security field. Before iris recognition, it is very important to search center of pupil. In recent years, there was developed many searching algorithms of center of pupil, but all most method are too many processing time. In this paper, we proposed a new method for searching center of pupil. This method is greatly reduced processing time about 30% compared with other algorithm using Hough transformation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.3C
• /
• pp.268-273
• /
• 2009

Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. In this paper, we propose a novel method based on local gradient orientation histogram which is robust to variations in illumination and rotations of iris patterns. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

• Convergence Security Journal
• /
• v.22 no.4
• /
• pp.141-146
• /
• 2022

The iris, a biometric information, is safe, unique, and reliable, such as fingerprints, and is personal information that can significantly lower the misrecognition rate than other biometric authentication. However, due to the nature of biometric authentication, it is impossible to replace it if it is stolen. There is a case in which an actual iris photo is taken and 3d printed so that the eyes work as if they were in front of the camera. As such, there is a possibility of iris leakage through high-definition images and photos. In this paper, we propose to improve iris masking performance by supplementing iris region masking research based on existing blurring techniques. Based on the results derived in this study, it is expected that it can be used for the security of video conference programs and electronic devices.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2004.05a
• /
• pp.24-27
• /
• 2004

An enhancement of tracking capacity to find a position of the Iris images is presented in this paper. The propose algorithm is called FFDP (Four Points Diagonal Positioning) that the image is positioned with arbitrary 4 points on the edge of iris and the selective 4 points are drawn by a diagonal line on the cross. The experiment result shows that the algorithm is efficient to track on the eyelid.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.332-335
• /
• 2005

A Study on the moving iris tracking and the screen cursor controlling is presented in this paper. The screen cursor is moved by center position of iris moving to extent of eye. The experimental result shows that the moving of iris and screen cursor are accord with distance and size of screen for the optimal tolerance is reduced the tracking error.

• Journal of information and communication convergence engineering
• /
• v.3 no.2
• /
• pp.110-113
• /
• 2005

An enhancement of tracking capacity for the centering position of eye and iris on the facial image is presented. A facial image is acquisitioned with a CCD camera to be converted into a binary image. The eye region to be a specified brightness and shapes is used the FRM method using the neighboring five mask areas, and the iris on the eye is tracked with FPDP method. The experimental result shows that the proposed methods lead the centering position tracking capability to be enhanced than the pixel average coordinate values method.

• Journal of information and communication convergence engineering
• /
• v.2 no.3
• /
• pp.202-204
• /
• 2004

An improvement of tracking capacity to find a position of the Iris images is presented in this paper. The propose algorithm is used the Four Points Diagonal Positioning algorithm that the image is positioned with arbitrary 4 points on the edge of iris and the selective 4 points are drawn by a diagonal line on the cross. The experiment result shows that the algorithm is efficient to track on the eyelid.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.43 no.2 s.308
• /
• pp.30-39
• /
• 2006

Iris recognition is that identifies a user based on the unique iris texture patterns which has the functionalities of dilating or contracting pupil region. Iris recognition systems extract the iris pattern in iris image captured by iris recognition camera. Therefore performance of iris recognition is affected by the quality of iris image which includes iris pattern. If iris image is blurred, iris pattern is transformed. It causes FRR(False Rejection Error) to be increased. Optical defocusing is the main factor to make blurred iris images. In conventional iris recognition camera, they use two kinds of focusing methods such as lilted and auto-focusing method. In case of fixed focusing method, the users should repeatedly align their eyes in DOF(Depth of Field), while the iris recognition system acquires good focused is image. Therefore it can give much inconvenience to the users. In case of auto-focusing method, the iris recognition camera moves focus lens with auto-focusing algorithm for capturing the best focused image. However, that needs additional H/W equipment such as distance measuring sensor between users and camera lens, and motor to move focus lens. Therefore the size and cost of iris recognition camera are increased and this kind of camera cannot be used for small sized mobile device. To overcome those problems, we propose method to increase DOF by iris image restoration algorithm based on focus value of iris image. When we tested our proposed algorithm with BM-ET100 made by Panasonic, we could increase operation range from 48-53cm to 46-56cm.