16 September 1999 Autonomous physics-based color learning under daylight
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Proceedings Volume 3826, Polarization and Color Techniques in Industrial Inspection; (1999) https://doi.org/10.1117/12.364314
Event: Industrial Lasers and Inspection (EUROPTO Series), 1999, Munich, Germany
Abstract
An autonomous approach for learning the colors of specific objects assumed to have known body spectral reflectances is developed for daylight illumination conditions. The main issue is to be able to find these objects autonomously in a set of training images captured under a wide variety of daylight illumination conditions, and to extract their colors to determine color space regions that are representative of the objects' colors and their variations. The work begins by modeling color formation under daylight using the color formation equations and the semi-empirical model of Judd, MacAdam and Wyszecki (CIE daylight model) for representing the typical spectral distributions of daylight. This results in color space regions that serve as prior information in the initial phase of learning which consists in detecting small reliable clusters of pixels having the appropriate colors. These clusters are then expanded by a region growing technique using broader color space regions than those predicted by the model. This is to detect objects in a way that is able to account for color variations which the model cannot due to its limitations. Validation on the detected objects is performed to filter out those that are not of interest and to eliminate unreliable pixel color values extracted from the remaining ones. Detection results using the color space regions determined from color values obtained by this procedure are discussed.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yves Berube Lauziere, Denis J. Gingras, Frank P. Ferrie, "Autonomous physics-based color learning under daylight", Proc. SPIE 3826, Polarization and Color Techniques in Industrial Inspection, (16 September 1999); doi: 10.1117/12.364314; https://doi.org/10.1117/12.364314
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