Puja S. Prasad¹, Adepu Sree Lakshmi¹, Sandeep Kautish², Simar Preet Singh³, Rajesh Kumar Shrivastava³, Abdulaziz S. Almazyad⁴, Hossam M. Zawbaa⁵, Ali Wagdy Mohamed^6,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 725-739, 2024, DOI:10.32604/cmes.2023.030640

Abstract Pupil dynamics are the important characteristics of face spoofing detection. The face recognition system is one of the most used biometrics for authenticating individual identity. The main threats to the facial recognition system are different types of presentation attacks like print attacks, 3D mask attacks, replay attacks, etc. The proposed model uses pupil characteristics for liveness detection during the authentication process. The pupillary light reflex is an involuntary reaction controlling the pupil’s diameter at different light intensities. The proposed framework consists of two-phase methodologies. In the first phase, the pupil’s diameter is calculated by applying stimulus (light) in one eye… More >

S. Navaneethan^1,*, P. Siva Satya Sreedhar², S. Padmakala³, C. Senthilkumar⁴

Computer Systems Science and Engineering, Vol.46, No.1, pp. 125-135, 2023, DOI:10.32604/csse.2023.034546

Abstract The pupil recognition method is helpful in many real-time systems, including ophthalmology testing devices, wheelchair assistance, and so on. The pupil detection system is a very difficult process in a wide range of datasets due to problems caused by varying pupil size, occlusion of eyelids, and eyelashes. Deep Convolutional Neural Networks (DCNN) are being used in pupil recognition systems and have shown promising results in terms of accuracy. To improve accuracy and cope with larger datasets, this research work proposes BOC (BAT Optimized CNN)-IrisNet, which consists of optimizing input weights and hidden layers of DCNN using the evolutionary BAT algorithm… More >

Waleed El Nahal¹, Hatim G. Zaini², Raghad H. Zaini³, Sherif S. M. Ghoneim^4,*, Ashraf Mohamed Ali Hassan⁵

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 33-50, 2022, DOI:10.32604/cmc.2022.028190

Abstract Recently, many researchers have tried to develop a robust, fast, and accurate algorithm. This algorithm is for eye-tracking and detecting pupil position in many applications such as head-mounted eye tracking, gaze-based human-computer interaction, medical applications (such as deaf and diabetes patients), and attention analysis. Many real-world conditions challenge the eye appearance, such as illumination, reflections, and occasions. On the other hand, individual differences in eye physiology and other sources of noise, such as contact lenses or make-up. The present work introduces a robust pupil detection algorithm with and higher accuracy than the previous attempts for real-time analytics applications. The proposed… More >

Pingping Yu¹, Wenjie Duan¹, Yi Sun², Ning Cao^{3, *}, Zhenzhou Wang¹, Guojun Lu⁴

CMC-Computers, Materials & Continua, Vol.64, No.2, pp. 1199-1217, 2020, DOI:10.32604/cmc.2020.010384

Abstract Human eye detection has become an area of interest in the field of computer vision with an extensive range of applications in human-computer interaction, disease diagnosis, and psychological and physiological studies. Gaze-tracking systems are an important research topic in the human-computer interaction field. As one of the core modules of the head-mounted gaze-tracking system, pupil positioning affects the accuracy and stability of the system. By tracking eye movements to better locate the center of the pupil, this paper proposes a method for pupil positioning based on the starburst model. The method uses vertical and horizontal coordinate integral projections in the… More >