Muhammad Furqan Rasyid, M. S. Mustafa, Andi Asvin Mahersatillah Suradi, M. Rizal, Mushaf Mushaf, Arham Arifin
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摘要

眼睛检测技术用于识别和分析一个人眼睛的独特特征,作为识别或验证其身份的一种方式。该技术可用于各种应用,如模式识别、生物识别系统、监视系统等。大多数应用都要求眼部检测的精度,因此需要一种快速可靠的眼部检测方法。在本研究中,提出了一种使用Python OpenCV和MediaPipe库的眼睛检测方法,与现有解决方案相比,该方法具有更好的准确性。这两个库都是用Python编程语言实现的,Python在软件开发人员中很受欢迎,因为它具有面向对象编程的能力,易于数据操作和处理,以及在人工智能等各个领域的库和模块的可用性。该系统使用智能手机拍摄的视频进行了测试。虽然这些视频是在不理想的条件下拍摄的,比如光线不完美,但我们对56个质量相对较好的视频进行了测试,这些视频持续了大约5-10秒。结果表明,该方法的准确率为100%。此外,该系统可以区分睁眼和闭眼状态,这将有助于进一步研究检测眨眼。综上所述,所建立的模型能够以非常高的准确率检测眼睛。
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Deteksi Mata di Video Smartphone Menggunakan Mediapipe Python
Eye detection technology is used to recognize and analyze unique features of a person's eyes as a way to identify or authenticate their identity. This technology can be used in various applications such as pattern recognition, biometric systems, surveillance systems, and others. Most applications require precision in eye detection, so a fast and reliable eye detection method is needed. In this research, an eye detection method is proposed using the Python OpenCV and MediaPipe libraries, which offer better accuracy compared to existing solutions. Both libraries are implemented in the Python programming language, which is popular among software developers for its ability in object-oriented programming, easy data manipulation and processing, and availability of libraries and modules in various fields such as artificial intelligence. The system was tested using videos captured using a smartphone. Although the videos were captured under suboptimal conditions, such as imperfect lighting, testing was conducted on 56 videos that had relatively good quality and lasted about 5-10 seconds. The results obtained showed an accuracy rate of 100%. Additionally, the system can distinguish between open and closed eye conditions, which will facilitate further research in detecting eye blinks. In conclusion, the model created can detect eyes with a very high accuracy rate.
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