Since the large diffusion of mobile devices with embedded camera and flashgun, the
red eye artifacts have de-facto become a critical problem. Red eyes are caused by the flash light
reflected off the blood vessels of the human retina. This effect is more pronounced when the flash
light is closer to the camera lens, which often occurs in compact imaging devices. To reduce these
artifacts, most cameras have a red-eye flash mode which fires a series of pre-flashes prior picture
acquisition. The biggest disadvantage of the pre-flash approach is power consumption (flash is the
most power-consuming part of imaging devices), and thus it is not suitable for power-constrained
systems (e.g., mobile devices). Moreover, this approach does not guarantee total prevention of red
eye artifacts. Red eye removal must then be performed in post-processing, through the use of automatic
correction algorithms. The aim of this Chapter is to depict the state of the art of automatic
detection and correction of red eyes, taking into account strong points and drawbacks of the most
well-known techniques, with particular emphasis on the image degradation risk associated to false
positives in red eye detection and to wrong correction of red eyes. Furthermore the problem of
estimating the quality of the final result, without reference image, is examined.
