In this paper we present a methodology to use Gabor response features for real-time visual road environment classification. Processing Gabor filters using hardware solely dedicated to this task enables improved real-time texture classification. Using such hardware enables us to successfully extract Gabor feature information for a four-class road environment classification problem. We used summary histogram as an intermediate level of texture representation prior to final classification. Overall we obtain a maximally correct classification circa 98%, outperforming prior work in the field.
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