2026-05-29T23:06:25Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/300872026-02-03T11:08:22Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Ruiz-Beltrán, Camilo Andrés author Romero-Garces, Adrian author González-García, Martín author Sánchez-Pedraza, Antonio author Rodríguez-Fernández, Juan Antonio author Bandera-Rubio, Antonio Jesús author 2022-05 The detection of a person’s eyes is a basic task in applications as important as iris recognition in biometric identification or fatigue detection in driving assistance systems. Current commercial and research systems use software frameworks that require a dedicated computer, whose power consumption, size and price are significantly large. This paper presents a hardware-based embedded solution for eye detection in real-time. From an algorithmic point-of-view, the popular Viola–Jones approach has been redesigned to enable highly parallel, single-pass image-processing implementation. Synthesized and implemented in an All-Programmable System-on-Chip (AP SoC), this proposal allows us to process more than 88 frames per second (fps), taking the classifier less than 2 ms per image. Experimental validation has been successfully addressed in an iris recognition system that works with walking subjects. In this case, the prototype module includes a CMOS digital imaging sensor providing 16 Mpixels images, and it outputs a stream of detected eyes as 640 × 480 images. Experiments for determining the accuracy of the proposed system in terms of eye detection are performed in the CASIA-Iris-distance V4 database. Significantly, they show that the accuracy in terms of eye detection is 100%. Camilo A. Ruiz-Beltrán, Adrián Romero-Garcés, Martín González, Antonio Sánchez Pedraza, Juan A. Rodríguez-Fernández, Antonio Bandera, Real-time embedded eye detection system, Expert Systems with Applications, Volume 194, 2022, 116505, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2022.116505. https://hdl.handle.net/10630/30087 https://doi.org/10.1016/j.eswa.2022.116505 Ojos - Reconocimiento Real-time embedded eye detection system