车牌检测识别--Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks

Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks
https://arxiv.org/abs/1709.08828

本文使用CNN网络来进行车牌检测和识别,一个网络完成端对端训练,检测和识别不用分离。
The whole framework takes 0.3 − 0.4 second per image on a Titan X GPU

车牌检测识别--Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks_第1张图片

网络流程如下所示:
车牌检测识别--Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks_第2张图片

首先使用 VGG-16 中的卷积层来提取特征,然后使用 Region Proposal Network (RPN) 来提取车牌候选区域,有了车牌区域,我们进行车牌识别,这里我们没有进行车牌分割, regard the plate recognition as a sequence labeling problem。

Bidirectional RNNs (BRNNs) with CTC loss [14] are employed to label the sequential features
车牌检测识别--Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks_第3张图片

识别效果图:

Performance Evaluation on PKUData
车牌检测识别--Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks_第4张图片

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