资源列表
kmean_Clustering
- k均值聚类分析 c++版本 完全和MATLAB相同-k-means clustering analysis of c++ version of the same full and MATLAB
AVIwriteread
- 这段程序可将AVI视频转换为bmp格式图片，并将bmp格式图片序列转换为avi视频文件。-This program can be converted to bmp format AVI video images, and bmp format for image sequence is converted to avi video files.
CodeInCForIdentifyCarID
- 这里是用c++编写的车牌识别的源代码！！1-Code In C++ For Identify the ID of Cars
BTC
- 非常重要的圖像壓縮BTC轉換 歡迎參考-BTC image compression is very important to welcome the reference to conversion
chameleon
- Chameleon is a new algorithm in Data Mining created by Kumar. It is based on ROCK and DBSCAN algorithms.
ColorFeatures
- 一种彩色图像的边缘检测算法，检测效果非常好，它是对Canny算法的改进，定位好，相应标准高，检测率高，误检率低-a kind of edge detection algorithm.The algoritlun employs amultpassprocessing approach that re}novesnoisefrom theRGB componentswith apre-filter, with the color edge detector then based on an ext
mbsb
- Matlab在图像处理与目标识别方面的应用 附有例题 1染色体识别与统计 2汽车牌照定位与字符识别 3 基于BP神经网络识别字符的简单实验-Matlab image processing and target recognition in the application of a chromosome with Example 2 License Plate Recognition and Statistical location and character recognition based
cpsb
- 车牌识别目前比较完善的源码 考虑了多种可能出现的识别问题并给出了解决方法 -License Plate Recognition relatively complete source code is currently considering a variety of possible identification of problems and gives a solution
Probing_into_Technique_of_Image_Enhancement_Based_
- ：图像增强是图像处理的一个重要分支，是图像边缘提取、图像分割等的基础．文章介绍了常用的图像增强技 术，并且以Madab为工具完成图像的直方图均衡化、巴特沃斯高通滤波器操作的示例，给出了处理前后的对照图像．重点介 绍了利用小波变换进行图像增强，获得了比较好的增强效果．-: Image enhancement is an important branch of image processing is the image edge extraction, image segmentation,
Face_detection_based_on_color_images
- 提出了一种基于肤色的精确人脸定位算法,详细叙述了在图片的颜色调整与肤色检测,肤色区域的平滑、 分割与填充,候选眼睛的选取及配对中遇到的具体问题并提出了解决方案. 本算法能较为准确地定位彩色图像 中的正面、小角度偏侧和旋转的人脸,还能检测出一幅图中的多个人脸.-Presents a human face based on skin color precision positioning algorithm, described in detail in the image color ad
trifix
- 一个用于计算图像边缘强度的matlab程序，可以用了检测图像边界-EDGE detecting
convexpolygon
- 输入N个点的坐标，判断这N个点能否构成一个凸多边形-Enter the coordinates of N points, N points to determine whether this constitutes a convex polygon