2026-05-28T10:05:14Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/236572026-02-03T10:56:19Zcom_10630_2254col_10630_37953

Real-time embedded eye detection system Ruiz-Beltran, Camilo Andres Romero-Garces, Adrian González-García, Martín Sánchez-Pedraza, Antonio Rodríguez-Fernández, Juan Antonio Bandera-Rubio, Antonio Jesús Procesado de imágenes - Técnicas digitales 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%. 2022-01-24T09:59:45Z 2022-01-24T09:59:45Z 2022-01-24T09:59:45Z 2022 journal article Expert Systems With Applications, 194 (2022) 116505 https://hdl.handle.net/10630/23657 10.1016/j.eswa.2022.116505 eng http://creativecommons.org/licenses/by-nc/4.0/ open access Atribución-NoComercial 4.0 Internacional Elsevier