Adaptive Road Recognition Technology for Unmanned Field Scenee
HUA Xia;WANG Xinqing;YU Yaowei;MENG Fanjie;MA Shaoye;WANG Dong;SHAO Faming;PLA Army Engineering University;
In order to realize the accurate and efficient identification of unstructured roads under the complex environment of unmanned equipment, this paper proposes an adaptive algorithm for field recognition in the field. The algorithm adds a new adaptive preprocessing algorithm to classify the field environment images and perform targeted preprocessing on different types of images. The image is divided from the pixel level to the regional level and divided into homogenous super pixel blocks. It combines the color,texture,position,and shape features with high discrimination in superpixel blocks,constructs a new superpixel block synthesis feature vector with higher discrimination,and improves the traditional Laplace support vector by dynamically selecting road identity samples. Machine algorithm,using the improved algorithm to learn and train the super pixel block classifier,successfully realized accurate and efficient recognition of roads in complex field scenes. The specified database detection results show that the road recognition accuracy is 91. 9%, and it has higher road detection accuracy and better real-time performance,and can accurately and effectively identify unstructured roads in the field.
【CateGory Index】： TP181;TP391.41