Vehicle recognition in infra-red images using parallel vision board.

Auteur(s)
Kagesawa, M. Ueno, S. Ikeuchi, K. & Kashiwagi, H.
Jaar
Samenvatting

This paper describes a method for vehicle recognition, in particular, for recognizing a vehicle's make and model. The system employs infra-red images so that the same algorithm can be used both day and night, The algorithm, based on the vector-quantization, was originally proposed by Krumm, and is implemented on an IMAP parallel image-processing board. The system makes the compressed database of local features, for the algorithm, of a target vehicle from given training images in advance; the system then matches a set of local features in the input image with those in training images for recognition. This method has the following advantages: it can detect even if part of the target vehicle is occluded; it can detect even if the target vehicle is translated due to running out of the lanes; and it does not require segmentation of vehicle part from input images. The above advantages have been confirmed by performing outdoor experiments. (A*)

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Publicatie

Bibliotheeknummer
C 19841 (In: C 19519 CD-ROM) /72 /73 / ITRD E110874
Uitgave

In: ITS: smarter, smoother, safer, sooner : proceedings of 6th World Congress on Intelligent Transport Systems (ITS), held Toronto, Canada, November 8-12, 1999, Pp-

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