Marked-line recognition is one of the important methods to realize the patrol Automatic Guided Vehicle (AGV) autonomous navigation. This paper will focus on a new method in marked-line recognition and it has good robustness in outdoor environment which the illumination is variation, the marked-line is partially-occluded, and the objects on the load are similar to the marked-line. Firstly, the feature points of the marked-line are extracted by using the color and contour features, and the feature points are used as vertexes to construct the network topological diagram G = (V, E). Secondly, the vertexes are clustered by using the slope and the slope change rate of the network edges, and the vertexes of each clustering are connected by polylines. Lastly, the subclasses are clustered again if the average slope and the average slope change rate of each subclass are similar. The class with the most vertexes is used to recognize marked-line. The experimental result demonstrates that the recognition accuracy is almost 100% under the variant illumination intensity and even if the marked-line with partial occlusion the recognition accuracy is about 98.5%, the experimental results show that the method has good robustness in complex outdoor environment. In addition, the method takes about 45ms and it has good real time performance.

The Marked-line Recognition Based on Network Topology Diagram Points Clustering

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The Marked-line Recognition Based on Network Topology Diagram Points Clustering