One-stage Vehicle Engine Number Recognition System

Cheng-Hsiung Yang, Han-Shen Feng
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引用次数: 1

Abstract

This study proposes a one-stage vehicle engine number recognition system which avoids using the traditional three-stage recognition procedures of positioning, segmentation, and then character recognition, without the needs of image preprocessing procedures, we directly locate and recognizes the text targets in the vehicle engine image. The experiment using 926 labeled images via transfer learning to train our prediction model and then using this prediction model to test another 2310 unlabeled images, the overall accuracy achieved 99.48% and the execution time for recognize a single image is 234ms.
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一级车辆发动机号码识别系统
本研究提出了一种一期汽车发动机编号识别系统,避免了传统的定位、分割、字符识别三阶段识别流程,不需要图像预处理流程,直接对汽车发动机图像中的文本目标进行定位和识别。实验使用926张带标签的图像通过迁移学习训练我们的预测模型,然后使用该预测模型测试另外2310张未标记的图像,总体准确率达到99.48%,单个图像识别的执行时间为234ms。
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