Abstract
The vision-based intelligent vehicle systems for environment perception have required integration of image data acquired from multiple cameras. We developed multiband camera, which can simultaneously obtain both images of visible color and near infrared. In this paper, we present a texture-based objects recognition under road environment scene using a multiband image. The new color feature is proposed to cluster meaningful regions of a multiband image and the texture segmentation is utilized in classification of texture-based objects. Experimental results show that the proposed method effectively recognizes the texture-based objects including roads, buildings, trees, and sky, as well as faces of pedestrians. In the future, by integrating the shape-based objects recognition, which includes pedestrians, cars, and bicycles with texture-based objects recognition, the proposed system can expand into a complex scene understanding system for vehicle environment perception.
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Kang, Y., Kidono, K., Kimura, Y., Ninomiya, Y. (2007). Texture-Based Objects Recognition for Vehicle Environment Perception Using a Multiband Camera. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4842. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76856-2_57
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DOI: https://doi.org/10.1007/978-3-540-76856-2_57
Publisher Name: Springer, Berlin, Heidelberg
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