Title:
StudyonStereoVision-basedCross-countryObstacleDete
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Description: Cross-country intelligent vehicles always work in
complicated environments with varying illuminations.
The paper presents a new cross-country obstacle
detection technology based on stereo vision system.
The original images are preprocessed by Gaussian
filter and contrast-limited adaptive histogram
equalization (CLAHE) method to weaken the effect of
noise, light and contrast. Harris corners are located
with sub-pixel accurate. To guarantee the overall
system real-time performance, feature-based matching
techniques are studied and fundamental matrix is
calculated based on random sample consensus
(RANSAC). Also restrains are studied to eliminate
pseudo matching pairs. Then data interpolation is
introduced to build elevation maps. Edge extraction
and morphological processing are concerned to
accomplish obstacle detection. Experiment results for
different conditions are presented in support of the
obstacle detection technology.
File list (Check if you may need any files):
StudyonStereoVision-basedCross-countryObstacleDetectionTechnology.pdf
