Resumo

JIMENEZ MORENO, Robinson; AVILES SANCHEZ, Oscar  e  AMAYA HURTADO, Darío. Driver distraction detection using machine vision techniques. Ing. compet. [online]. 2014, vol.16, n.2, pp.55-63. ISSN 0123-3033.

This article presents a system for detecting states of distraction in drivers during daylight hours using machine vision techniques, which is based on the image segmentation of the eyes and mouth of a person, with a front-face-view camera. From said segmentation states of motion of the mouth and head are established, thus allowing to infer the corresponding state of distraction. Images are extracted from short videos with a resolution of 640x480 pixels and image processing techniques such as color space transformation and histogram analysis are applied. A decision concerning the state of the driver is the result from a multilayer perceptron-type neural network with all extracted features as inputs. Achieved performance is 90% for a controlled environment screening test and 86% in real environment, with an average response time of 30 ms

Palavras-chave : Distraction; image processing; neural network; machine vision.

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