搜索资源列表
1122threading
- 一个新的算法，实现灰度图像的二值化分割，对于传统的分割，此算法效果甚好-A new algorithm, the binary gray image segmentation, the traditional segmentation, this algorithm was very good effect
chengxu-
- 图像处理的相关程序，有边缘检测，灰度变化，图像增强，二值化分割等-Image processing procedures, there are edge detection, gray scale, image enhancement, thresholding segmentation
shili6
- 通过图像的算法，实现图像的阈值处理，二值化分割，滤波，目标得到和目标分割等功能-Through the algorithm of image, realize the image threshold processing, two threshold segmentation, filtering, goals are and target segmentation etc. Function
demo
- 这是一个很完整，功能强大的程序，利用MFC集成了数字图像处理中所有基本的处理方法，如滤波，边缘检测，图像分割，图像二值化等等！-This is a very complete and powerful program, integrated digital image processing approach, such as filtering, edge detection, image segmentation, image binarization
83897655openCV
- 实现车牌识别，包括图像二值化，图像分割，图像弱化-License Plate Recognition
opencvCar
- 基于opencv的车牌识别程序，能实现目标跟踪，截图，车牌识别包括了打开图像、图像二值化、车牌定位、字符分割、字符识别等。-Opencv-based license plate recognition program, to achieve the target tracking shots, license plate recognition, including the open image, image binarization, license plate localization, c
Kapur_seg
- 使用Kapur算法（图像最大熵值）实现灰度图像的二值化分割-Using Kapur algorithm implements image binary segmentation
matlab-code
- 应用Matlab工具箱演示对比度增强，局部平滑，中值滤波，小波工具，边缘检测，图像二值化，Hough变换直线提取，灰度阈值分割，四叉树分裂合并法等，并完成这些处理程序的GUI集成。-Application the Matlab toolbox Demo contrast enhanced local smoothing, median filtering, wavelet tools, edge detection, image value, Hough transform line extra
20121116
- 数字图像处理：如灰度变换、图像增强、图像滤波、图像二值化及图像分割等。程序可运行。-Digital Image Processing: gray-scale transformation, image enhancement, image filtering, image binarization and image segmentation. The program can be run.
source-code
- Visiual C++ 数字图像处理（第二版）光盘包括图像分割，图像配准，图像二值化处理，图像的边缘检测-Visiual C++ Digital Image Processing (Second Edition) CD-ROM includes image segmentation, image registration, image binarization processing, image edge detection
source-code
- Visiual C++ 数字图像处理（第二版）光盘包括图像分割，图像配准，图像二值化处理，图像的边缘检测-Visiual C++ Digital Image Processing (Second Edition) CD-ROM includes image segmentation, image registration, image binarization processing, image edge detection
source-code
- Visiual C++ 数字图像处理（第二版）光盘包括图像分割，图像配准，图像二值化处理，图像的边缘检测-Visiual C++ Digital Image Processing (Second Edition) CD-ROM includes image segmentation, image registration, image binarization processing, image edge detection
OTSU1
- 。图像分割算法中最大类间方差法(OTSU)实现图像二值化,可以将图像分为目标类和背景类，便于后续处理。-. Image segmentation algorithm Otsu method (OTSU) for image binarization, image can be divided into the target class and background class, easy to subsequent processing.
CSharpUsefulCode
- 新手适用：C#常用代码合集 含42段实用代码，如：s扫描器调用、win7判断管理员身份、打开指定路径文件对话框、获取页面源代码、图像二值化、正则分割字符串-Novice applicable: C# code Collection contains 42 segments common utility code, such as: s scanner call, win7 judge an administrator, open the dialog box, specify the path
threshold
- 基于CVI，打开一幅图像，显示对应的直方图，选择二值化分割阈值的方法，将会自动计算出对应的阈值，进行二值分割。可以保存处理后的图像。-Based CVI, open an image display corresponding to the histogram, binary segmentation method to select the threshold value, it will automatically calculate the threshold value correspo
Vehicle-license-recognition
- 车牌识别最基本的流程是：将采集后的图像二值化，然后依次经过车牌定位、字符分割、去除干扰，最后是字符识别-License Plate Recognition basic process is: after the acquisition of image binarization, followed through the license plate location, character segmentation, remove interference, and finally charact
otsu
- 大津算法代码，进行自适应阈值分割，用于图像二值化-Otsu' s method code, adaptive thresholding for image binarization
myOtsu
- 本程序主要是利用大津法实现图像的二值化分割。与基本大津法不同的地方在于，本程序需要分割的是车辆底部的阴影区域，所以除了使用谷底法外还限制了计算范围，也就是利用了多层二值化分割的灰度值范围限制。-This program is to segment images using OTSU method. Also, it combine valley and multiply threshold methods.
matlab-code
- backgroundsubtractionGUI.m 实现背景差分方法的基本GUI界面设置 diedaierzhihua.m 用迭代分割的方法实现图像二值化 foreground.m 背景差分方法中前景图的构建 mianhuizhi.m 图像可视化中ct、mri图像的三维面绘制方法 rotate3d.m 图像可视化中对ct、mri图像进行面绘制并旋转 video2image.m 从视频中批量截取多帧图像 weicaise.m 对图像进行伪彩色处理-backgroundsu
zhiwenshibieyuchuli
- 本代码是用来对指纹图像进行预处理的，包括图像分割，图像二值化，图像细化等。-This code is used to pre process the fingerprint image, including image segmentation, image binarization, image thinning and so on.