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毕业论文网 > 任务书 > 机械机电类 > 测控技术与仪器 > 正文

复杂图表的字符检测与识别任务书

 2020-05-06 16:41:32  

1. 毕业设计(论文)的内容和要求

随着计算机科学技术的迅速发展,其在工业工程领域中的应用也越发广泛。

在实际工程设计中,工程图纸作为重要一环,是工作人员进行施工的信息依据,而将图纸中的关键信息录入到计算机中也是一项较为常见的工作内容。

但由于工程图纸通常数量多,内容复杂,传统人为识别并录入的方法工作效率较低,且出错率较高。

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2. 参考文献

1]洪汉玉, 章秀华, 林志敏等,基于结构特征的高温、高热钢坯端面字符识别[J]. 微电子学与计算机, 2009, 5(26): 219-222. [2]Dai, Y., Ma, H., Liu, J., Li, L. A high performance license plate recognition system based on the web technique[C]. Proceedings of IEEE Intelligent Transportation Systems, 2001: 325-329. [3]Rami Al-Hmouz, Subhash Challa. License plate localization bases on a probabilistic model[J]. Machine Vision and Applications, 2010, 21: 319-330. [4]Nicol#225;s Fernando Gazc#243;n, Carlos Iv#225;n Ches#241;evar, Silvia Mabel Castro. Automatic vehicle identification for Argentinean license plates using intelligent template matching[J]. Pattern Recognition Letters, 2012, 33: 1066-1074. [5]Yuh-Rau Wang, Wei-Hung Lin, Shi-Jinn Horng. A sliding window technique for efficient license plate localization based on discrete wavelet transform[J]. Expert Systems with Application, 2011, 38: 3142-3146. [6]李国平, 路长厚, 李健美. 基于 Canny 算子字符边缘检测与分割方法研究[J]. 机床与液压, 2007, (12): 42-44. [7]熊哲源, 樊晓平, 黎燕. 基于数学形态学边缘检测的车牌字符分割算法[J]. 计算机系统应用, 2010, (09): 155-158. [8]刘洋, 薛向阳, 路红, 郭跃飞. 一种基于边缘检测和线条特征的视频字符检测算法[J]. 计算机学报, 2005, (03): 427-433. [9]Nicolas Thome, Antoine Vacavant, Lionel Robinault, Serge Miguet. A cognitive and video-based approach for multinational License Plate Recognition[J]. Machine Vision and Applications, 2011, 22: 389-407. [10]C. Zhang, G. Sun, D. Chen, T. Zhao. A Rapid Locating method of vehicle license plate based on characteristics of characters#8217; connection and projection[C]. Proceedings of the Second IEEE Conference on Industrial Electronics and Applications, 2007: 2546-2549. [11]D. S. Kim, S. I. Chien. Automatic car license plate extraction using modified generalized symmetry transform and image warping[C]. Proceedings of the IEEE International Symposium on Industrial Electronics, 2001: 2022-2027. [12]Fukushima K. Neocognitron: A self-organizing neural network model for amechanism of pattern recognition unaffected by shift in position [J].Biological cybernetics, 1980, 36(4): 193-202. [13]Le Cun Y, Jackel L D, Bottou L, et al. Comparison of learning algorithms for handwritten digit recognition [C]//International Conference on Artificial Neural Networks(ICANN), 1995, 60: 53-60. [14]Le Cun Y, Jackel L D, Bottou L, et al. Comparison of learning algorithms for handwritten digit recognition [C]//International Conference on Artificial Neural Networks(ICANN), 1995, 60: 53-60. [15]Ph#7841;m D V. Online handwriting recognition using multi convolution neural networks [M]//Simulated Evolution and Learning. Springer Berlin Heidelberg,2012: 310-319. [16]Kussul E, Baidyk T. Improved method of handwritten digit recognition tested on MNIST database[J]. Image and Vision Computing, 2004, 22(12): 971-981. [17]Guyon I, Schomaker L, Plamondon R, et al. UNIPEN project of on-line data exchange and recognizer benchmarks [C]//IEEE International Conference on Pattern Recognition(ICPR), 1994, 2: 29-33. [18]Ahranjany S S, Razzazi F, Ghassemian M H. A very high accuracy hand written character recognition system for Farsi/Arabic digits using convolutionalneural networks [C]//IEEE Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010: 1585-1592. [19]Ciresan D C, Meier U, Gambardella L M, et al. Convolutional neural network committees for handwritten character classification[C]//IEEE International Conference on Document Analysis and Recognition (ICDAR), 2011:1135-1139. [20]Yuan A, Bai G, Jiao L, et al. Offline handwritten English character recognition based on convolutional neural network [C]//IEEE International Workshop on Document Analysis Systems, 2012: 125-129.

3. 毕业设计(论文)进程安排

起讫日期 设计(论文)各阶段工作内容 12.20-1.20 明确和细化任务,选择和确定方案;着手进行文献检索和开题报告;确定翻译内容,完成翻译 1.21-2.10 开题报告;完成系统功能和软件方案设计 2.11-4.28 仿真软件编程、测试、完善 4.29#8212;5.25 毕业论文写作 5.26-6.17 准备毕业设计答辩、毕业设计答辩

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