Abstract
This paper describes a method for recognizing partially occluded objects to realize a bin-picking task under different levels of illumination brightness by using the eigen-space analysis. In the proposed method, a measured color in the RGB color space is transformed into the HSV color space. Then, the hue of the measured color, which is invariant to change in illumination brightness and direction, is used for recognizing multiple objects under different levels of illumination conditions. The proposed method was applied to real images of multiple objects under different illumination conditions, and the objects were recognized and localized successfully.
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© 1997 Springer-Verlag Berlin Heidelberg
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Ohba, K., Sato, Y., Ikeuchi, K. (1997). Appearance based visual learning and object recognition with illumination invariance. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63931-4_245
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DOI: https://doi.org/10.1007/3-540-63931-4_245
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Online ISBN: 978-3-540-69670-4
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