基于深度学习的智能路牌识别系统设计  

Design of intelligent road card recognition system based on deep learning

作　　者：林付春 刘宇红 张达峰 张荣芬 Lin Fuchun;Liu Yuhong;Zhang Dafeng;Zhang Rongfen(College of Big Data and Information Engineering,Guizhou University,Guiyang 550025,Chin)

机构地区：[1]贵州大学大数据与信息工程学院,贵州贵阳550025

出　　处：《电子技术应用》2018年第6期68-71,共4页Application of Electronic Technique

摘　　要：提出了一种基于机器视觉和深度学习的智能路牌识别系统。采用嵌入式的ARM9作为前端采集系统,在服务器上采用图像处理算法先对前端采集的路牌图像进行文字区域的提取和分割,然后用训练好的卷积神经网络对分割的文字进行识别,最后将识别信息以语音的形式反馈给使用者。使用前端硬件在高速公路上采集路牌图像并在服务器的CAFFE框架上进行测试,结果表明该系统能实时准确地将路牌信息以语音的方式播报给使用者。This paper proposed a scheme design of intelligent road card recognition system based on machine vision and deep learning. ARM9 is used as the part of front-end collection system, the image processing algorithm is used to complete the area ex-traction and segmentation of the road card text from the front-end acquisition image, the deep learning with a convolutional neural network is used to recognize the text in the cloud server, and the speech of the text information is presented to the user. Using the front-end hardware to get the road card images on the high way, the function of our system under CAFFE framework on the server is tested and the results show that the system can broadcast the road card information effectively to the user in real time.

关 键 词：路牌识别 机器视觉 深度学习 卷积神经网络 CORTEX-A9 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]