计算技术与自动化2024，Vol.43Issue(2)：116-122,7.DOI:10.16339/j.cnki.jsjsyzdh.202402020
基于深度信任网络模型的乌东选煤厂铁路车号图像识别方法
Image Recognition Method of Railway Car Number of Wudong Coal Preparation Plant Based on Deep Trust Network Model
尉维洁 1齐健 2周南 2刘化男 2高会颖3
作者信息
- 2. 国家能源集团 新疆能源有限责任公司洗选中心,新疆维吾尔自治区 乌鲁木齐 830000
- 3. 天津美腾科技股份有限公司,天津 300000
- 折叠
摘要
Abstract
Accurate identification of railway vehicle number can provide basis for coal plant loading,thus ensuring the efficient and smooth completion of the loading process.Therefore,a method of railway vehicle number image recognition based on deep trust network model in Wudong Coal Preparation Plant is proposed.Firstly,the original vehicle number image is collected by high-speed camera equipment,and the image boundary is detected by Sobel operator;Then,based on the font stroke width characteristics of the train number,a stroke width transformation algorithm is used to locate and determine the train number area in the image,and the LBP algorithm is used to extract features within the train number area;Finally,the extracted features are input into the deep trust network model.After training the network model and constantly updating the parameters,the vehicle number image is accurately recognized.The experiment shows that this method can accurately recog-nize the train number image of Wudong Coal Preparation Plant.In the deep trust network model,when the restricted Boltz-mann network is 4 layers and the number of hidden layer nodes is 128,the model has the strongest classification recognition ability,the minimum training loss and the best performance.关键词
深度信任网络/边界检测/车号定位/图像识别/笔画宽度变换/特征提取Key words
deep trust network/boundary detection/vehicle number positioning/image recognition/stroke width change/feature extraction分类
信息技术与安全科学引用本文复制引用
尉维洁,齐健,周南,刘化男,高会颖..基于深度信任网络模型的乌东选煤厂铁路车号图像识别方法[J].计算技术与自动化,2024,43(2):116-122,7.
