中文字符识别系统的研究与实现

为提高字符识别率，将 DAG-SVM(Directed Acyclic Graph Support Vector Machine)算法应用于字符识别， 提出了一种基于 DAG-SVM 的 OCＲ(Optical Character Ｒecognition) 中文字符识别系统，分别对图像预处理、 分割，字符识别 3 个模块进行了研究与实现。图像预处理采用图像滤波、灰度化处理、图像归正; 图像分割包 括二值化处理、横向及纵向分割; 字符识别模块对当前流行的三大类算法进行了研究，选用 DAG-SVM 作为字 符识别的算法，并基于 Matlab 进行了实现及验证。结果表明该系统 OCＲ 字符识别率达 92． 86%。

Dynamic Extend Paths Algorithm for Wireless Sensor Network

In order to improve the recognition rate，the DAG-SVM(Directed Acyclic Graph Support Vector Machine) algorithm is applied to character recognition，and an OCＲ(Optical Character Ｒecognition) system based on DAG-SVM，which can be divided into three components is proposed． Algorithms of image pre- processing，image segmentation and OCＲ are researched． Image pre-processing，the first part，contains image filtering，graying and tilt correction． And the second component is image segmentation，which contains binaryzation and segmentation from two sides． The last part is character recognition，whose main algorithms is researched and DAG-SVM is choosed． The system is simulated by Matlab，and the results show that the recognition rate is 92． 86% ．