TY - CHAP
T1 - A visual perception approach for accurate segmentation of light profiles
AU - Carozza, Ludovico
AU - Bevilacqua, Alessandro
AU - Gherardi, Alessandro
PY - 2009
Y1 - 2009
N2 - In this paper we present the automatic real time segmentation algorithm we devised to be consistent with human visual perception for a highly contrasted scene, like the one generated by the projection of the luminous profiles from high power sources on a uniform untextured pattern. An accurate identification of shadow-light profiles is required, for example, from industrial diagnostics of light sources, in compliance with regulations for their employment by human users. Off-the-shelf CCD technology, though it could not be able to cover the wide dynamic range of such scenes, could be successfully employed for the geometric characterization of these profiles. A locally adaptive segmentation algorithm based on low-level visual perception mechanisms has been devised and tested in a very representative case study, i.e the geometrical characterization of beam profiles of high power headlamps. The evaluation of our method has been carried out by comparing (according to a curve metric) the extracted profiles with the ones pointed out by five human operators. The experiments prove that our approach is capable of adapting to a wide range of luminous power, mimicking visual perception correctly even in presence of low SNR for the acquired images.
AB - In this paper we present the automatic real time segmentation algorithm we devised to be consistent with human visual perception for a highly contrasted scene, like the one generated by the projection of the luminous profiles from high power sources on a uniform untextured pattern. An accurate identification of shadow-light profiles is required, for example, from industrial diagnostics of light sources, in compliance with regulations for their employment by human users. Off-the-shelf CCD technology, though it could not be able to cover the wide dynamic range of such scenes, could be successfully employed for the geometric characterization of these profiles. A locally adaptive segmentation algorithm based on low-level visual perception mechanisms has been devised and tested in a very representative case study, i.e the geometrical characterization of beam profiles of high power headlamps. The evaluation of our method has been carried out by comparing (according to a curve metric) the extracted profiles with the ones pointed out by five human operators. The experiments prove that our approach is capable of adapting to a wide range of luminous power, mimicking visual perception correctly even in presence of low SNR for the acquired images.
U2 - 10.1007/978-3-642-02611-9_17
DO - 10.1007/978-3-642-02611-9_17
M3 - Chapter (peer-reviewed)
SN - 978-3-642-02610-2
VL - 5627
T3 - Lecture Notes in Computer Science
SP - 168
EP - 177
BT - Image Analysis and Recognition
PB - Springer
T2 - 6th International Conference on Image Analysis and Recognition 2009
Y2 - 6 July 2009 through 8 July 2009
ER -