本程序中，利用了LBP特征对人脸特征进行提取，并且利用SVM对提取的人脸特征进行训练和识别，其中，所用的图像处理库为 OpenCV2.4.9版本；通过对人脸库中的标准标本进行测试，算法识别率高达95%以上；

c++写的姓名识别程序，里边有项目要求和源代码，供学习使用

地名识别程序 地名识别程序 地名识别程序 地名识别程序 地名识别程序

仅作为学习和练习的用途，不作为毕设以及其他商业用途。

matlab程序，包含了基本LBP，旋转不变LBP，均匀LBP ,旋转不变均匀LBP，CLBP等的LBP算子提取和分类，基于AR的人脸库，还有附加的一个说明文档以及自己测试的一些结果分析。

涉及的知识点：Python、调用百度API、PyQt5 运行环境：Mac+Python3.7+PyQt5

网上找的人脸识别程序，JAR文件，可以用反编译软件查看代码，学习人脸识别的同学可以参考下

强大的纯Java车牌识别程序源码, 功能非常全，而且是纯java编写，不含杂质。

Algorithm Description Recognizing objects from large image databases, histogram based methods have proved simplicity and usefulness in last decade. Initially, this idea was based on color histograms that were launched by swain [1]. This algorithm presents the first part of our proposed technique named as “Histogram processed Face Recognition” [2] For training, grayscale images with 256 gray levels are used. Firstly, frequency of every gray-level is computed and stored in vectors for further processing. Secondly, mean of consecutive nine frequencies from the stored vectors is calculated and are stored in another vectors for later use in testing phase. This mean vector is used for calculating the absolute differences among the mean of trained images and the test image. Finally the minimum difference found identifies the matched class with test image. Recognition accuracy is of 99.75% (only one mis-match i.e. recognition fails on image number 4 of subject 17) [1] M. J. Swain and D. H. Ballard, “Indexing via color histogram”, In Proceedings of third international conference on Computer Vision (ICCV), pages 390–393, Osaka, Japan, 1990. [2] Fazl-e-Basit, Younus Javed and Usman Qayyum, "Face Recognition using processed histogram and phase only correlation ", 3rd IEEE International Conference on Emerging Technology pp. 238-242

车牌号识别，内容包括主程序、子程序、字符模板和实验报告，采用matlab语言。