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opengl中关于拾取感兴趣区域
- opengl中关于拾取感兴趣区域
图像感兴趣区域自动提取算法
- 图像感兴趣区域自动提取算法
OSTU.这是一个阈值分割算法
- 这是一个阈值分割算法，主要用来对图像进行二值化，提取感兴趣区域~~,This is a threshold segmentation algorithm, mainly used for binary images, extract region of interest ~ ~
showroi.rar
- 提取感兴趣区域的演示程序,有GDI界面的,方便实用.,Demo
xiququyu.rar
- 感兴趣区域提取，能用于车牌号及台风等图像，效果不错,Extract the interesting area, it can be used in license plate number and typhoons images and so on, has good results
cbuilder
- 刚兴趣区域的提取与保存~~在C++builder环境下进行的 对图片感兴趣区域进行的提取与保存-image
ROI
- 感兴趣区域提取。根据人感兴趣的区域对图像进行裁减-Region of interest extraction. According to people interested in the process of reducing the region' s image
Matlab
- Matlab图像感兴趣区域编码,这是个非常好用的程序-Matlab region of interest image coding, this is a very useful procedure
1
- 实现动态规划算法和感兴趣区域提取，效果不错啊 -The realization of dynamic programming algorithm and region of interest extraction, the effect of good ah
roispline
- 采用B样条曲线分割感兴趣区域，有兴趣的可以看一下-The use of B-spline curve divided region of interest, interested can look at
MyPick2
- opengl中关于拾取感兴趣区域的程序2.-opengl in the region of interest on the pick-up procedures 2.
SaliencyToolbox2.2
- 视觉注意力模型，寻找感兴趣区域，模仿人眼找出最感兴趣的区域，再找出第二感兴趣的区域，以此类推-Visual attention model to find the region of interest, to imitate the human eye to identify the most interesting region, and then find the second region of interest, and so on
roidpoly
- 感兴趣区域提取,已通过实验证其可行性以及实用性-region of interest detect
demodetect
- 提取感兴趣区域的演示程序,有GDI界面的,方便实用.-Demo
121
- 本文提出一种提取感兴趣区域的模型，结合三方面的信息，做出感兴趣区域的魔板，运用于视频研究-This paper presents a model region of interest extraction, combined with three aspects of information, to make the magic region of interest board, used in video research
exa4_4
- 在OPENCV 环境下，对图片进行的处理，主要包括选取感兴趣区域并截取-under the enviroment of opencv,a photo is processed.the interesting area is cut.
Matlab
- Matlab图像感兴趣区域编码 -Matlab image region of interest coding
regionofinterest
- 感兴趣区域算法描述 感兴趣区域算法描述-interest
ImageSearchingBasedonAOI
- 基于感兴趣区域的纹理检索方式，其中的区域自动提取方式很不错-Image Searching Based on AOI
感兴趣区域
- 用matlab提取图形中的的感兴趣区域，其他区域全部变成白色(Extract the region of interest for the graph)