【作者】 邬建瓴；

【导师】 何南忠；

【作者基本信息】 华中科技大学 ， 计算数学， 2006， 硕士

【摘要】 数字识别有着广泛的应用前景。本文介绍了数字识别研究的实际背景、理论意义,以及本文的研究工作等,介绍了两种典型的数字识别算法:基于BP神经网络的识别算法和基于结构特征的识别算法,讨论了印刷体数字识别和基于手写数字识别的主要应用。对于印刷体数字识别,讨论了一个具体的应用例子:扫描等高线图纸上的数字识别,并提出了一种能够有效地提取扫描等高线图纸中数字并进一步识别的方法。等高线图纸中包含大量的数字注记,正确提取并识别这些数字是图纸矢量化处理中的重要组成部分。本文先用改进的模板匹配的方法提取并初步识别其中的数字,再用特征提取法进一步识别不同的数字。实验结果表明,该算法速度较快、精度高,且有一定的抗干扰性。对于手写体数字识别,本文给出了一个具体的应用例子:学生成绩单中的数字识别。文中对手写体数字的提取及识别的基本原理和方法作了介绍,并用MATLAB工具实现了手写体数字识别系统的主要功能。本文先用MATLAB的函数提取出成绩单中的数字,然后选取数字的结构特征和笔划特征并采用模板匹配的方法达到识别数字的目的,实验结果表明,基于所用结构模型和知识库的识别方法对规范手写体数字是可行的,具有较高的识别率及较好的抗噪性能,也可以识别一定条件下的自由手写体数字。为了提高识别率和可靠性,除了增强对噪声的滤除能力外,还要增大知识库,这些都有待我们进一步的研究。更多还原

【Abstract】 Digital recognition has the extensively applied foreground. In this paper, we introduce the actual background and the theory meaning and the research work on digital recognition, we introduce two typical algorithms for digital recognition: the recognition algorithm based on BP neural network and the recognition algorithm based on structure characteristic, we discuss the main application on printed digital recognition and handwriting digital recognition.A specific applied example is discussed for printed digital recognition: digital recognition for the scanned contour drawing. And we put forward a method that can extract the numbers in the drawing efficiently and further recognize these numbers. It includes a great deal of numeral notes in the contour drawing, extracting correctly and recognizing these numbers is an important part in the drawing vector processing. In this paper, we present an advanced method of template matching to extract and recognize the numbers, and then we use the feature extraction method to further recognize different numbers. Experiments show that the speed of the algorithm is quick and the accuracy is high and it has certain anti-interference. A specific applied example is raised for handwriting digital recognition: digital recognition in student’s report card. We introduce the basic principle and methods for the handwriting digital extracting and recognition. And we realize the main function of handwriting digital recognition system using the MATLAB. We extract the numbers in the report card using the function of MATLAB, then we select the structure characteristic and the stroke characteristic of the numbers and we present the method of template matching to attain the purpose of recognizing numbers, experiments show that the method based on structure model and knowledge bases is viable for the normative handwriting digital, it also can recognize free handwriting digital under certain condition. In order to enhance recognition rate and reliability, in addition to strengthen the ability of filtering, we still need to enlarge the knowledge base, these all need our further research.更多还原