文件名称:StudyonStereoVision-basedCross-countryObstacleDete
- 所属分类:
- 图形图像处理(光照,映射..)
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- [PDF]
- 上传时间:
- 2012-11-26
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- 949kb
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- 提 供 者:
- 晓*
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本文提出了一种新的跨国家的障碍
检测技术为基础的立体视觉系统。
原始图像的预处理的高斯
过滤器和对比度限制的自适应直方图
均衡( CLAHE )方法来削弱作用 噪音,光线和对比度。哈里斯的角落位于与子像素精确。
-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.
检测技术为基础的立体视觉系统。
原始图像的预处理的高斯
过滤器和对比度限制的自适应直方图
均衡( CLAHE )方法来削弱作用 噪音,光线和对比度。哈里斯的角落位于与子像素精确。
-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.
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StudyonStereoVision-basedCross-countryObstacleDetectionTechnology.pdf