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首页> 外文会议>International Wireless Communications and Mobile Computing Conference >Recognition of Casting Embossed Convex and Concave Characters Based on YOLO v5 for Different Distribution Conditions
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Recognition of Casting Embossed Convex and Concave Characters Based on YOLO v5 for Different Distribution Conditions

机译：基于YOLO V5的铸造压花凸面和凹陷的识别不同的分布条件

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摘要

Traditional casting character recognition algorithms need to select appropriate position features for different scenes in the character location step, so it is difficult to realize the recognition task of casting embossed concave and convex characters in the different distribution in complex scenes. In this letter, a recognition method of casting embossed characters based on YOLO v5 is proposed. The fast and reliable depth learning algorithm YOLO v5 is used to automatically extract the image features and realize the recognition of casting embossed characters (including numbers and letters) Recognition. The experimental results show that the accuracy of the network model for steel seal character recognition is higher than traditional computer vision algorithms, the average processing time of the algorithm is quickly, and the weight file volume is small, which meets the accuracy and efficiency requirements of engineering application.
机译：传统的铸造字符识别算法需要为角色位置步骤中的不同场景选择适当的位置特征，因此很难实现在复杂的场景中不同分布的铸造压花凹凸和凸字符的识别任务。 在这封信中，提出了一种基于YOLO V5的铸造压花角色的识别方法。 快速可靠的深度学习算法YOLO V5用于自动提取图像特征，并实现铸造压花字符（包括数字和字母）识别的识别。 实验结果表明，钢封字符识别的网络模型的准确性高于传统的计算机视觉算法，算法的平均处理时间很快，重量文件量小，符合精度和效率要求 工程应用。

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