Laser & Optoelectronics Progress, Volume. 56, Issue 3, 031010(2019)
Obstacle Recognition in Vegetation Environment Based on Markov Random Field
In order to identify foliage and the adjacent obstacles in the vegetation scenes, an object detection algorithm of three-dimensional laser radar is proposed. The neighborhood characteristics of neighboring points are constructed in point cloud, and new characteristic parameters are extracted as determining criterion. Then the Gaussian mixture model is obtained by using the maximum expectation algorithm to characterize the distribution of the parameters. Finally, the priori model is established by using Markov random field. The optimal objective function is obtained by the graph-cut method under the maximum posteriori probability framework. This algorithm has been successfully applied to the unmanned platform. The experimental results show that the algorithm can effectively identify foliage and their adjacent obstacles, and the boundaries of obstacles can be detected clearly. Compared with traditional algorithms, the proposed algorithm is more robust and accurate, and its response time meets the demand of practical applications.
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Ziyang Cheng, Guoquan Ren, Yin Zhang. Obstacle Recognition in Vegetation Environment Based on Markov Random Field[J]. Laser & Optoelectronics Progress, 2019, 56(3): 031010
Category: Image Processing
Received: Jul. 30, 2018
Accepted: Aug. 31, 2018
Published Online: Jul. 31, 2019
The Author Email: Ren Guoquan (rrrgggqqq@163.com)