基于改进跳蛛算法的二维OTSU限重标志识别算法

针对交通标志识别中限重标志和限速标志相似程度大、容易造成误检等问题，结合抗噪能力强的二维OTSU自动阈值分割法与寻优能力强的跳蛛优化算法，提出了一种基于跳蛛优化的二维OTSU限重标志识别算法。该算法通过统计交通标志牌感兴趣区域的二维灰度直方图，采用改进跳蛛算法求解二维OTSU分割阈值，快速地实现交通标志图像的二值化，再利用DBSCAN对二值化图像边缘点聚类，最后根据聚类结果的相对位置正确识别限重标志。实验结果表明：在不降低识别率的条件下，运算时间降低了34.16%,并能够正确区别限重标志和限速标志。

Two-dimensional OTSU Weight Limit Sign Recognition Algorithm Based on Improved Jumping Spider Algorithm

In view of the large similarity between the weight limit sign and the speed limit sign, which is easy to cause false detection and other problems, combining the two-dimensional OTSU automatic threshold segmentation method with strong anti-noise ability and the Jumping Spider Optimization Algorithm (JSOA) with strong searching ability, a two-dimensional OTSU weight limit sign recognition algorithm based on improved JSOA is proposesd. The algorithm counted the two-dimensional gray histogram of region of interest of traffic signs, solved the threshold of segmentation of two-dimensional OTSU using the improved jumping spider algorithm, quickly realized the binarization of traffic sign images, used DBSCAN to cluster the edge points of the binarization image, and finally correctly identified the weight limit sign according to the relative position of the clustering results. The experimental results show that the operation time is reduced by 34.16% without reducing the recognition rate, and the weight limit sign and speed limit sign can be correctly distinguished.