Abstract
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.
This research has been partly granted by SIMPESFAIP SPA.
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Bevilacqua, A., Gherardi, A., Carozza, L. (2009). A Visual Perception Approach for Accurate Segmentation of Light Profiles. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2009. Lecture Notes in Computer Science, vol 5627. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02611-9_17
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DOI: https://doi.org/10.1007/978-3-642-02611-9_17
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