This paper presents the image processing sub-module, part of the in-car embedded system, designed by the CMM in the framework of the European PROMETHEUS project. In this project, the authors' task is to extract road information in dynamic scenes. In particular, the authors have to perform road/lane segmentation and obstacle detection in real-time. To reach this goal, the authors have studied and developed dedicated algorithms and a multi-pipeline processor especially designed for their implementation. The morphological transformations are supported by two pipeline processors built around powerful morphological ASICs: PIMM1. The road/lane segmentation algorithm runs in background on the main pipeline processor. The second pipeline processor is dedicated either to obstacle detection or to on-request processing such as indicator detection. A very important item of the morphological sub-module, the multi-access image memory board, supplies the two pipeline processors with image data. The intelligent board working under the multi-tasking VxWorks operating system configures via a VSB bus the morphological sub-module. Such a multi-pipeline processor allows very high speed image processing compatible with real-time performances.
[1]
Jean Serra,et al.
Image Analysis and Mathematical Morphology
,
1983
.
[2]
Xiangzhan Yu,et al.
ROAD RECOGNITION IN COMPLEX TRAFFIC SITUATIONS
,
1994
.
[3]
Michel Bilodeau,et al.
Road segmentation and obstacle detection by a fast watershed transformation
,
1994,
Proceedings of the Intelligent Vehicles '94 Symposium.
[4]
S. BEUCHER,et al.
ROAD SEGMENTATION BY WATERSHEDS ALGORITHMS
,
1990
.
[5]
Serge Beucher,et al.
Watershed, Hierarchical Segmentation and Waterfall Algorithm
,
1994,
ISMM.
[6]
Michel Bilodeau,et al.
Road tracking, lane segmentation and obstacle recognition by mathematical morphology
,
1992,
Proceedings of the Intelligent Vehicles `92 Symposium.