Abstract
A parallel architecture for road scene classification is presented. The system is designed to classify scenes on the basis of road curvature and operate in daytime, highway environments. The system processes input in five stages and uses the same decision-making paradigm, Hough transforms, in all three higher levels of processing. Many parallel implementations of Hough transforms have already been developed [3, 7]. In addition, we present our own implementation, which expands the algorithm to more general feature detection applications. Using only algorithms that are easily implemented in VLSI (very large scale integrated) circuitry, we develop a powerful real-time image processing module for autonomous steering control.
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© 1992 Springer-Verlag New York, Inc.
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Polk, A., Jain, R. (1992). A Parallel Architecture for Curvature-based Road Scene Classification. In: Masaki, I. (eds) Vision-based Vehicle Guidance. Springer Series in Perception Engineering. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2778-6_14
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DOI: https://doi.org/10.1007/978-1-4612-2778-6_14
Publisher Name: Springer, New York, NY
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