资源列表
zlib1.zip
- 包含可用于C语言的zlib.lib和zlib.h
VBZIP
- 用VB调用ZIP.dll和unzip.dll实现文件的压缩和解压缩。-VB and unzip.dll ZIP.dll called a file compression and decompression.
Jpeg2000CodecUseJava
- 站长！这是一老外用Java写的Jpeg2000编解码程序，较全面详细。请查收！-head! This is a foreigner writing Java Jpeg2000 codec procedures, a more comprehensive detail. Please find!
canbus(FPGA)
- 基于FPGA的can 总线设计，采用verilog语言编写。在FPGA的开发环境下，新建一个工程，然后将本文件中的各个源代码添加进工程里，即可运行仿真。-FPGA-based bus design can use verilog language. FPGA development environment, a new project, and then the paper all the source code to add the project, Simulation can be run
Sample-2.3-20110710
- OpencvSharp是一个高效的OpenCV的C#版本，本资源是OpencvSharp最新版本的相关例程，具有很高的参考价值！-OpencvSharp is an efficient C# version of OpenCV, the resource is OpencvSharp latest version of the routines, a high reference value!
opencvDigitRecognize
- 基于opencv的数字识别系统，能通过模板准确识别数字-Opencv-based digital identification systems, accurate identification numbers through a template
ImageProcessing(openCV)
- 一个基于openCV的图像处理程序，包含有边缘检测，图像匹配，形态学变换，金字塔采样，视频采集，相机标定等各种函数。-OpenCV-based image processing program includes edge detection, image matching, morphological transformation, the pyramid samples, video capture, camera calibration and other functions.
视频监控（面积报警）
- 通过视频监控，对视频流帧处理，自动发现火情并报警。-Through video surveillance, video streaming frame processing, auto-discovery and fire alarm.
Distortion Correction
- VC+opencv 实现建筑物梯形畸变校正 radon变换 sobel边缘检测 直方图均衡图像增强 radon直线检测 仿射变换等算法-VC+ opencv trapezoidal distortion correction to achieve the building radon transform sobel edge detection image enhancement histogram equalization radon affine transform line detecti
SubPixelEdgeDetect
- 使用OPENCV编写的亚像素边缘提取，其中包括运行所需库，及测试数据；可直接运行。-Written using OPENCV subpixel edge detection, including running the needed libraries, and test data Can be run directly.
matlab_grabcut-master
- 用MATLAB实现了GrabCut的图像分割的源代码供参考-Using MATLAB to achieve the GrabCut image segmentation of the source code for reference
cnn_evaluation_smoke-master
- 此代码简单易学，能有效检测烟雾，识别率高，机器学习。(This code is easy to learn, can effectively detect smoke, high recognition rate, machine learning.)