Mask RCNN Methods for Eyes Modelling
DOI:
https://doi.org/10.18517/ijods.2.2.63-68.2021Keywords:
eye, mask RCNN, object detection, webcam, OpenCVAbstract
Object detection is one of Deep Learning section in Computer Vision. The application of computer vision is divided into image classification and object detection. Object detection have target to find specific object from an image. The application of object detection for security are face recognition, and face detection. Face detection have been developed for medical application to identify emotion from faces. In this research, we proposed an eye modelling by using Mask RCNN. The eye model was applied in real time detection combined with OpenCV. The dataset was created from online dataset and image from webcam. The model was trained with 4 epochs and 131 iterations. The final model was successfully detected eye from real-time application.
References
N. Mohammad, Z. Omar, E. Supriyanto, A. Dietzel, and J. Haueisen, “Automated detection of microaneurysm for fundus images,” IECBES 2016 - IEEE-EMBS Conf. Biomed. Eng. Sci., pp. 600–605, 2017, doi: 10.1109/IECBES.2016.7843520.
R. Senthamizh Selvi, D. Sivakumar, J. S. Sandhya, S. Siva Sowmiya, S. Ramya, and S. Kanaga Suba Raja, “Face recognition using Haar - Cascade classifier for criminal identification,” Int. J. Recent Technol. Eng., vol. 7, no. 6, pp. 1871–1876, 2019.
H. Hendrick, “The Halal Logo Classification by Using NVIDIA DIGITS,” in International Conference on Applied Information Technology and Innovation (ICAITI), 2018, pp. 162–165.
H. Hendrick, W. Zhi-Hao, C. Hsien-I, C. Pei-Lun, and J. Gwo-Jia, “IOS mobile APP for tuberculosis detection based on chest X-ray image,” Proc. ICAITI 2019 - 2nd Int. Conf. Appl. Inf. Technol. Innov. Explor. Futur. Technol. Appl. Inf. Technol. Innov., pp. 122–125, 2019, doi: 10.1109/ICAITI48442.2019.8982152.
G.-J. Jong, Hendrick, Z.-H. Wang, K.-S. Hsieh, and G.-J. Horng, “A Novel Feature Extraction Method an Electronic Nose for Aroma Classification,” IEEE Sens. J., vol. PP, no. c, pp. 1–1, 2019, doi: 10.1109/JSEN.2019.2929239.
Hu Xiaoyan, Ji Zhenyu, You Fusheng, Long Keping, and Peng Yunfeng, “Study on Disease Screening and Monitoring System Based on Wireless Communication and IOT,” 2012 Spring Congr. Eng. Technol., pp. 1–6, 2012, doi: 10.1109/SCET.2012.6341961.
M. Pamplona Segundo, L. Silva, O. R. P. Bellon, and C. C. Queirolo, “Automatic face segmentation and facial landmark detection in range images,” IEEE Trans. Syst. Man, Cybern. Part B Cybern., vol. 40, no. 5, pp. 1319–1330, 2010, doi: 10.1109/TSMCB.2009.2038233.
G. Zheng, X. Wu, Y. Hu, and X. Liu, “Object detection for low-resolution infrared image in land battlefield based on deep learning,” Chinese Control Conf. CCC, vol. 2019-July, pp. 8649–8652, 2019, doi: 10.23919/ChiCC.2019.8866344.
J. Redmon and A. Farhadi, “YOLO v.3,” Tech Rep., pp. 1–6, 2018, [Online]. Available: https://pjreddie.com/media/files/papers/YOLOv3.pdf.
R. Senthamizh Selvi, D. Sivakumar, J. S. Sandhya, S. Siva Sowmiya, S. Ramya, and S. Kanaga Suba Raja, “Face recognition using Haar - Cascade classifier for criminal identification,” Int. J. Recent Technol. Eng., vol. 7, no. 6, pp. 1871–1876, 2019.
H. Hendrick, “The Halal Logo Classification by Using NVIDIA DIGITS,” in International Conference on Applied Information Technology and Innovation (ICAITI), 2018, pp. 162–165.
H. Hendrick, W. Zhi-Hao, C. Hsien-I, C. Pei-Lun, and J. Gwo-Jia, “IOS mobile APP for tuberculosis detection based on chest X-ray image,” Proc. ICAITI 2019 - 2nd Int. Conf. Appl. Inf. Technol. Innov. Explor. Futur. Technol. Appl. Inf. Technol. Innov., pp. 122–125, 2019, doi: 10.1109/ICAITI48442.2019.8982152.
G.-J. Jong, Hendrick, Z.-H. Wang, K.-S. Hsieh, and G.-J. Horng, “A Novel Feature Extraction Method an Electronic Nose for Aroma Classification,” IEEE Sens. J., vol. PP, no. c, pp. 1–1, 2019, doi: 10.1109/JSEN.2019.2929239.
Hu Xiaoyan, Ji Zhenyu, You Fusheng, Long Keping, and Peng Yunfeng, “Study on Disease Screening and Monitoring System Based on Wireless Communication and IOT,” 2012 Spring Congr. Eng. Technol., pp. 1–6, 2012, doi: 10.1109/SCET.2012.6341961.
M. Pamplona Segundo, L. Silva, O. R. P. Bellon, and C. C. Queirolo, “Automatic face segmentation and facial landmark detection in range images,” IEEE Trans. Syst. Man, Cybern. Part B Cybern., vol. 40, no. 5, pp. 1319–1330, 2010, doi: 10.1109/TSMCB.2009.2038233.
G. Zheng, X. Wu, Y. Hu, and X. Liu, “Object detection for low-resolution infrared image in land battlefield based on deep learning,” Chinese Control Conf. CCC, vol. 2019-July, pp. 8649–8652, 2019, doi: 10.23919/ChiCC.2019.8866344.
J. Redmon and A. Farhadi, “YOLO v.3,” Tech Rep., pp. 1–6, 2018, [Online]. Available: https://pjreddie.com/media/files/papers/YOLOv3.pdf.
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Published
2021-12-31
How to Cite
[1]
R. Hidayat, Hendrick, Riandini, Z.-H. . Wang, and H. . Gwo-Jiun, “Mask RCNN Methods for Eyes Modelling”, Int. J. Data. Science., vol. 2, no. 2, pp. 63–68, Dec. 2021.
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