搜索资源列表
ColorSpaceConverter
- 用于颜色空间的转换。可以在RGB, YPbPr, YCbCr, YUV, YIQ, YDbDr, JPEG-YCbCr, HSV, HSL, XYZ, CIE Lab (CIELAB), CIE Luv (CIELUV), and CIE Lch (CIELCH)等颜色空间中任意转换。 -The Matlab program used for color space conversion. In RGB, YPbPr, YCbCr, YUV, YIQ, YDbDr, JPEG-YCbCr,
meanshiftsegmentation
- 均值漂移图像分割测试程序,使用meanshift算法对彩色图像进行聚类分割，效果很好，并且显示使用时间、找到的类数，另包含RGB与LUV颜色空间的互相转换，图片矩阵数据转为降维数组等，程序中有详尽的注释和说明，并且配有测试结果图片，非常适合计算机视觉、机器学习、模式识别的朋友参考-failed to translate
luv2rgb.m.tar
- LUV to RGB function in MATLAB.
watershed-segmentation
- 分水岭分割算法代码；基于LUV颜色空间；C++语言编写-watershed based image segmentation algorithm
luv
- My first project...any comments are welcome
i_lab2luv
- Convert from Lab to Luv.
ColorTransform
- 用GDAL写的颜色变换功能 RGB和HIS\LUV\LAB之间的转换-ColorTransform code
rgb2luv
- 实现了RGB彩色空间到LUV空间的转换，其原理可见http://blog.csdn.net/kit_147/article/details/5485470-Convert RGB to LUV
OpenCV-trans-color
- 以OPENCV做的各種色彩轉換空間，有 RGB to gray, RGB to HSV, RGB to Lab, RGB to Luv, RGB to Ycbcr -To do a variety of color conversion OPENCV Space, RGB to gray, RGB to HSV, RGB to Lab, RGB to Luv, RGB to Ycbcr
ImageInfo
- 图像的颜色通道转换代码实现（RGB to XYZ、HSV、HSL、LAB、LUV、YCbCr等）-Image conversion code color channels (RGB to XYZ, HSV, HSL, LAB, LUV, YCbCr, etc.)
csma-ca
- check it out dude... u r really gonna enjoy this. trust me... luv u
xyz2luv
- for converting image to LUV color space
luv
- 基于ARM11的运动背景的黄色小球的实时捕获与跟踪代码，芯片是S3C6410，没有采用OPENCV代码而是直接跟踪处理，基于色彩空间的跟踪程序-Target tracking based on ARM11 camera, the development board to use the fly Ling ARM11, S3C6410 program, mainly is the moving background, yellow ball tracking.
featureExtract
- matlab实现的图像RGB转LUV后CM获取和Edge Direction Histogram的获得-matlab achieved after transfection LUV CM RGB image acquisition and Edge Direction Histogram obtained
Color-Convert
- 颜色空间转换RGB、LUV、Lab、HSV、HSI、YUV-color space convert RGB、LUV、Lab、HSV、HSI、YUV
ae602a9c136a
- 均值漂移图像分割测试程序,使用meanshift算法对彩色图像进行聚类分割，效果很好，并且显示使用时间、RGB与LUV颜色空间的互相转换(Mean shift image segmentation test procedures, the use of meanshift algorithm for color images clustering segmentation, the effect is very good, and show the use of time, find the c