Real-time embedded eye detection system - Ruiz-Beltrán, Camilo Andrés; Romero-Garces, Adrian; González-García, Martín; Sánchez-Pedraza, Antonio; Rodríguez-Fernández, Juan Antonio; Bandera-Rubio, Antonio Jesús (Elsevier, 2022)
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%.
Keywords: Ojos - Reconocimiento; Eye detection; Viola–Jones algorithm; All programmable System-on-Chip