资源列表
img2bits
- 读取图像变换成二进制码流的matlab代码-Read image is converted into a binary stream matlab code
bits2img
- 将处理过的二进制比特流写入图像，保存显示-The treated binary bit stream to write the image
sift
- sift图像特征提取 vs2010+opencv2.2 如果想搞清原理，请参照如下内容： http://blog.csdn.net/zddmail/article/details/7521424 -sift image feature extraction vs2010+ opencv2.2 If you want to find out the principles, please refer to the following: http://blog.csdn.net/z
TB_IMGVITDEC
- 对图像加入白噪声干扰，用维特比译码进行去扰，分别用硬判决和软判决，显示出的图像可以看出不同的效果-White noise is added to the image, performed using Viterbi decoding descrambling, respectively, with the hard decision and soft decision, showing the different effects can be seen in the image
graph
- 输出页面，图形图像的处理，数字图像处理菜单栏功能的实现数据库操作-printing graph
steerable_filters
- Implements the 1st and 2nd order Gaussian derivative steerable filter in matlab.The oriented first order derivative can be obtained by taking the dot product of a unit vector oriented in a specific direction with the gradient. The basis filters are
6bd0e1629f2d
- 车辆检测，利用高斯滤波后对图像进行灰度及二值化，最后利用团块跟踪进行车辆的检测。-Vehicle detection, after the image using the Gaussian filter and binarizing the gray, and finally the use of briquettes tracing the vehicle is detected.
OpenCV_VS2010
- OpenCV 是一个功能强大的计算机视觉库，要用好它，除了要具有相关的计 算机视觉理论知识外，还需要具有一定的编程能力。本书作者通过对 OpenCV 中 文论坛中的大量问题观察，发现有很大比例的问题是因为用户对 C/C++语言不熟 练，导致出错， 或出错后不知如何解决。如果对 C/C++语言不熟悉，那使用 OpenCV 时会满头雾水瞎摸索，费心费力。 在这一章中，将介绍一些编程的基本概念， 让读者对编程的流程有一个基本 了解。这样在出现错误时，可以快速确定错误的类型，并知
OpenCV_CL
- opencv 自学材料有很多C语言版本的例子-There are a lot of self-study materials opencv C language version of the example
stitching_detail
- stitching_detail功能的讲解和代码实例-The stitching_detail function explanation and code examples
OpenCVAdaboost__
- 目前支持这种分类器的boosting技术有四种： Discrete Adaboost, Real Adaboost, Gentle Adaboost and Logitboost。-Currently support this classifier boosting technology, there are four: Discrete Adaboost, Real Adaboost, Gentle Adaboost and Logitboost.
Harris_Good_Features_to_Track
- Harris角点检测基本思想从图像局部的小窗口观察图像特征角点定义窗口向任意方向的移动都导致图像灰度的明显变化 - Observation of local image features the image widget Mobile corners definition window in any directi