资源列表
Pcl_object_recognition
- 基于PCL库的图像实时识别，PCL（Point Cloud Library）是在吸收了前人点云相关研究基础上建立起来的大型跨平台开源C++编程库，它实现了大量点云相关的通用算法和高效数据结构，涉及到点云获取、滤波、分割、配准、检索、特征提取、识别、追踪、曲面重建、可视化等。支持多种操作系统平台，可在Windows、Linux、Android、Mac OS X、部分嵌入式实时系统上运行-Image library based on real-time identification PCL, PCL
vqsplit
- it is vector quantization
word-segmentation
- 使用扫描方法对粘连在一起的文字进行分割处理，最后识别出来-Using the scanning method to stick together word segmentation, and finally identified
gaborPNeural-network-face-detection
- 基于gabor变换的，神经网络人脸识别，准确率较高。-Face recognition based on gabor transform and neural network, the accuracy is higher
NumberRecognition
- 采用模板匹配法进行手写数字的识别，是手写识别的基本方法，是学习手写识别技术的基础-To recognize handwritten numbers using the template matching method is the basic method for handwriting recognition, handwriting recognition technology is the basis of learning
RecogGUI
- 字符识别程序及其图形界面设计，读者可以方便的在界面进行操作，学习字符识别过程-Character recognition program and its graphical interface design, the reader can easily interface to operate, learn character recognition process
bpshuzi
- 通过Matlab基于BP神经网络实现数字0~9的识别。首先创建50个训练样本供网络学习，根据训练样本的特点确定输入层、输出层神经元个数，并确定隐含层神经元个数，完成对BP神经网络的设计；然后将训练样本输入BP网络中，完成对网络的训练；最后通过20个测试样本测试训练完成的网络性能，并显示识别结果。-Digital recognition based on BP neural network.First according to the characteristics of th
Projective-reconstruction-image
- 在Matlab图像处理工具箱中的Phantom函数，可以产生Shepp －Logan的大脑图，该图作为一个测试图，可反映人大脑的许多性质-In the Phantom function in Matlab image processing toolbox, can generate Shepp - Logan brain figure, the figure as a test pattern, can reflect the brain s many properties
pca_lda
- PCA + LDA 人脸识别，照着论文写得，大家可以参考-PCA+ LDA face recognition, according to paper to write, you can reference
ISODATA
- 用C++语言实现ISODATA算法，在VS2005下编译过没问题。-Achieve ISODATA algorithm using C++ language, compiled under VS2005 no problem.
Training
- 汉字验证码训练源码，，新手朋友们可以学习一下谢谢了第一次发贴-Chinese characters, training verification code source code, novice friends can learn about for the first post
suzishibie
- 用MATLAB读取图片，并用神经网络进行训练，输出辨识数字。-Reads the image using MATLAB, and training, the digital output identification using neural networks.