Unstructured road identification method

Abstract

The invention discloses an unstructured road identification method, which comprises the steps of: S1, acquiring a color image in front of a mobile robot in the running process, and preprocessing the acquired color image; S2, performing region segmentation on the image obtained by preprocessing; S3, performing edge detection on the preprocessed image; S4, and performing fusion extraction on the image obtained after edge detection, so as to obtain road regions. The unstructured road identification method is implemented by the steps of: firstly, acquiring the color image in front of the mobile robot, and preprocessing the acquired color image; secondly, subjecting the image to region segmentation, and extracting edge features; and finally, fusing region segmentation and edge feature information to obtain the road regions. According to the unstructured road identification method, an OTSU algorithm is adopted in region segmentation, a multi-directional sobel operator edge detection algorithm is adopted in edge detection, the time complexity is small, the algorithms have good identification effect for a new environment, the robustness thereof is greatly enhanced, and the precision and validity of calculation are improved.

Description

technical field [0001] The invention belongs to the field of computer vision, in particular to an unstructured road recognition method. Background technique [0002] At present, the world is in an "intelligent era", and intelligent technologies including intelligent information acquisition, intelligent information processing and intelligent human-computer interaction technology are and will continue to profoundly change people's lives. my country has proposed the strategic deployment of "Made in China 2025", the core of which is to improve the intelligence level of the manufacturing industry. [0003] While traditional smart technologies have brought about tremendous changes to the economy and society, there are still many development bottlenecks. These bottlenecks have made it difficult to cope with the requirements of the modern information society for massive and complex information processing, so a new generation of intelligent revolution is just around the corner. In ...

AI Technical Summary

Problems solved by technology

The application obtains the contour image directly through preprocessing, without effective processing, resulting in serious noise pollution of the contour image, which cannot effectively reflect the contour of the road area; using brightness information as the contour to distinguish roads from non-roads is easily affected by the environment The impact of using template matching increases the workload, and the effectiveness of the new environment algorithm will be weakened. At the same time, due to the complex conditions such as lighting, shadows, water marks, and fallen leaves on unstructured roads, the effect of the template is greatly reduced. Detection speed is also not guaranteed

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