资源列表
MIT_face_data
- 本文件是MIT人脸数据库，对于向研究人脸识别，人脸检测的朋友，可以下载，快来下载吧。-This document is the MIT face database, to study for face recognition, face detection friend, you can download, Come download it.
location
- 使用时打开目录下pic中的图片，然后依次单击按钮“转”、“1”、“2”、“3”、“4”和“5”，就可以实现精确的车牌定位。-Use this example to open directory pic in the picture, then click the button "turn", "1", "2", "3", "4" and "5", you can achieve precise positioning plates.
Visual-CPP-MATLAB
- 《Visual C++ MATLAB图像处理与识别实用案例精选》胡小锋，赵辉编着.本书系统介绍图像处理与识别的基本原理、典型方法和使用技术。-This book introduces the basic image processing and recognition principles, typical methods and use of technology.
graph-conversion
- 源代码包含三个文件，其中二个为计算机图形学中图形的平移和旋转源代码，第三个文件juzhen.h为头文件-Source code contains three documents, including two for the graphics computer graphics source code translation and rotation, and the third for the header file juzhen.h
filling
- 包含了多边形区域填充，扫描线种子填充，扫描线种子填充变形，简单种子填充，简单填充，基本包含了图形学中所有的填充-Contains a polygon fill, scan line seed filling, the scan line seed fill deformation, simple seed filling, simple filling, basically contains all of the padding graphics
curved-surface-and-curve
- 包含了曲线和曲面的源代码，曲线被认为图形学的基础，而曲面则是对曲线的扩展-Contains the curves and surfaces of the source code, graphics curve is considered the foundation of the surface is the extension of the curve
Image-segmentation-method
- 图像的区域分割法 经测试可以运行 手动获得种子-Image segmentation method
graphchop
- 英国sussex大学图像研究所James Malcolm博士写的Graphchop，matlab+C++环境可以运行-British Institute of Image sussex university, Dr. James Malcolm wrote Graphchop, matlab+C++ environment can be run
(ok)NHLIScode
- Tae Hoon Kim教授的Nonparametric Higher-Order Learning for Interactive Segmentation源码-Tae Hoon Kim, Professor Nonparametric Higher-Order Learning for Interactive Segmentation
msers
- MSER(删诞mauy stable extremal re舀ons)算法，提出一种对图像的尺度、旋转、仿 射变换更加稳定的区域不变量提取的算法。对于输入图像采用多尺度MSER提取算法，并对 提取的MsERS依据其灰度变换的平稳性对提取区域进行修正。提高了区域提取的可重复性 和匹配概率。-MSER (delete birth mauy stable extremal re scoop ons) algorithm is proposed to image the scale, rot
codeCVPR09fixed
- A Tensor-Based Algorithm for High-Order Graph Matching 张量空间上的高阶能力优化-A Tensor-Based Algorithm for High-Order Graph Matching tensor space optimization of high-level capabilities
struct_predict_smooth_v1.342
- Daniel Munoz的论文Contextual Classification with Functional Max-Margin Markov Networks-Daniel Munoz paper Contextual Classification with Functional Max-Margin Markov Networks