电子学报2011，Vol.39Issue(10)：2366-2371,6.
基于交叉视觉皮质模型的非结构化道路检测算法
An Unstructured Lane Detection Algorithm Based on Intersecting Cortical Model
摘要
Abstract
A lane detection algorithm is proposed using intersecting cortical model (ICM) in view of the weak universality and high complexity of the traditional methods in detecting the unstructured lane whose circumstance is complex and diverse. ICM has the superiority which is much closer to the information processing mechanism of biological vision. The ICM can distinguish ob jects and background dynamically according to the relevance between pixel and its neighbor pixels. As the best threshold and cyclic iterative times of ICM is artificially given it can not realize segmentation automatically. Therefore the decision mechanism of the minimum cross entropy is introduced to determine the cyclic iterative times and the best threshold automatically. The result of exper iments show that the precision of the algorithm is high,and it also has very strong adaptability to some unconventional lanes.关键词
非结构化道路/图像分割/交叉视觉皮质模型/最小交叉熵Key words
unstructured lane/image segmentation/intersecting cortical model (ICM)/minimum cross-entropy分类
信息技术与安全科学引用本文复制引用
高庆吉,张磊..基于交叉视觉皮质模型的非结构化道路检测算法[J].电子学报,2011,39(10):2366-2371,6.基金项目
国家自然科学基金项目(No.60776811) （No.60776811）
中央高校基本科研业务费中国民航大学专项(No.ZXH 2009B002) （No.ZXH 2009B002）
