Research of Obstacle Recognition Technology in Cross-Country Environment for Unmanned Ground Vehicle | Zendy

Yibing Zhao | Zendy; Hongbin Xu | Zendy; Lie Guo | Zendy; Linhui Li | Zendy; Mingheng Zhang | Zendy

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Research of Obstacle Recognition Technology in Cross-Country Environment for Unmanned Ground Vehicle

Author(s) -

Yibing Zhao,

Hongbin Xu,

Lie Guo,

Linhui Li,

Mingheng Zhang

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/531681

Subject(s) - artificial intelligence , obstacle , robustness (evolution) , computer science , computer vision , naive bayes classifier , segmentation , algorithm , color space , preprocessor , feature (linguistics) , pattern recognition (psychology) , image (mathematics) , geography , support vector machine , biochemistry , chemistry , linguistics , philosophy , archaeology , gene

Being aimed at the obstacle recognition problem of unmanned ground vehicles in cross-country environment, this paper uses monocular vision sensor to realize the obstacle recognition of typical obstacles. Firstly, median filtering algorithm is applied during image preprocessing that can eliminate the noise. Secondly, image segmentation method based on the Fisher criterion function is used to segment the region of interest. Then, morphological method is used to process the segmented image, which is preparing for the subsequent analysis. The next step is to extract the color feature S, color feature a and edge feature “verticality” of image are extracted based on the HSI color space, the Lab color space, and two value images. Finally multifeature fusion algorithm based on Bayes classification theory is used for obstacle recognition. Test results show that the algorithm has good robustness and accuracy

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