With the progress of science and technology, intelligent automation equipment is gradually applied to the production and life of the entire society. Significant progress has been made in the research of intelligent vehicles, the development and application of automatic recognition and lane recognition. In the future, with the increasing demand for recognition accuracy and speed, research in the field of track line recognition will become increasingly popular. There are many algorithms for detecting track lines, but when comparing the advantages and disadvantages of different algorithms, some problems were found, such as poor robustness of track line detection, and poor real-time track line detection due to the influence of other signal lines. Based on the original classic algorithm, this article expands the scope of use, improves the speed of trajectory detection and recognition, and improves the speed without affecting the effectiveness of trajectory detection. At present, fuzzy and multi-modal detection problems are the biggest problems encountered by classical Hugh transform and are strongly influenced by noise. This article will improve the Hugh transform to enhance the robustness and adaptability of the detection results.

Yuanyuan Dai, Shan Su, Linxin Cai. Design and Implementation of Lane Line Detection Algorithm Based on Image Recognition. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 12: 152-157. https://doi.org/10.25236/AJCIS.2023.061218.

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