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chap7.rar
- 医学图像处理，绝得能用的细胞边缘检测，分割最佳阈值的迭代算法，轮廓提取受噪声影响的分析,Medical image processing, the cells must have to use edge detection, segmentation optimal threshold of iterative algorithm, contour extraction affected by noise analysis
vc_imageprocessing
- VC++图像处理程序,哈弗变换，边缘检测，差影法，轮廓提取与跟踪，模板匹配，投影法，图像复原，阈值分割，种子填充等。-VC++ Image processing procedures, Haversian transform, edge detection, and poor shadow law, contour extraction and tracking, template matching, projection, image recovery, threshold segmentat
EdgeContour
- 对加载的图像进行轮廓识别，边缘检测（包括robert算子，sobel算子，prewitt算子等）的VC++程序-Of the loaded image contour recognition, edge detection (including robert operator, sobel operator, prewitt operator, etc.) VC++ program
EdgeContour
- VC数字图像处理典型算法及实现,完整的源码,主要算法有:Robert 算子,Sobel 算子,Prewitt 算子,Kirsch 算子,Gauss-Laplace 算子实现边缘检测 Hough变换,轮廓提取,轮廓跟踪-VC typical digital image processing algorithm and the realization of the complete source code, the main algorithm are: Robert operator,
Demo_Program
- 数字图像处理比较完整的程序，包括图像二值化、灰度线性化、阈值变换、边缘检测、轮廓跟踪、图像细化-More complete digital image processing procedures, including image binarization, gray linear, threshold transform, edge detection, contour tracing, image thinning, etc.
myfinalwork
- 实现第十章中采用Hough变换来检测图像中圆的过程。并对我提供的一幅灰度图像（sweden-coins.bmp），通过包括平滑（把细节去除），边缘检测（得到轮廓）以及Hough变换得到的圆，并把结果叠加到原来的灰度图像上。给出具体的过程，中间结果，最后结果，实现的代码，并写出报告-Implement Chapter Hough transform to detect the use of the image circle of the process. And I offer a graysca
initialactivecontour
- 用MATLAB编写的主动轮廓提取算法，该算法能对图像中的目标轮廓进行高效检测-Written by MATLAB active contour extraction algorithm that can image the efficient detection of object contour
GaitRsystem
- 实现人体步态检测和基于步态的人体身份识别算法，主要内容包括背景的提取，人体运动区域检测，人体轮廓提取，步态特征的提取，相似性度量和分类识别-Detection of the realization of human gait and gait-based human identification algorithms, including the background of the main contents of the extraction, detection of human motio
Image-Processing
- vc++数字图像编程基础，包括点运算、几何变换（平移、旋转、缩放、镜像）、正交变换（沃尔什、傅里叶、离散余弦）、图像增强（图像平滑、中值滤波、梯度锐化、拉普拉斯锐化）、形态学变换（腐蚀、膨胀、开、关）、边缘与轮廓（robert、sobel、frewit、kirsch、gauss-laplace边缘检测算子，hough变换，轮廓提取，轮廓跟踪）、图像分析（阈值分割、投影检测、差影检测、模板匹配）、图像复原（卷积模糊、逆滤波复原、维纳滤波复原，随机、椒盐噪声）、图像编码（赫夫曼编码、香农费诺编码、行
touch_1.01
- 图象边沿检测-提取-轮廓跟踪算法源代码-Image edge detection- Extraction- contour tracking algorithm source code
jpeg+mghe+mkou+sima+touch+wgttut+xchange
- jpeg_0.77.zip JPEG压缩编码系统源代码 mkou_1.0.zip 图案抖动技术处理系统源代码 touch_1.01.zip 图象边沿检测-提取-轮廓跟踪算法源代码 xchange_1.03.zip 图象几何变换算法源代码 sima_1.07.zip 图象模板匹配算法源代码 mghe_0.23.zip 图象平滑处理系统源代码 wgttut_5.0.zip 图形色彩量子化及材质压缩程序源代码 -jpeg_0.77.zipJPEG
eagedetectandfigureoperate
- 图像边缘与轮廓运算包括 // RobertDIB() - robert边缘检测运算 // SobelDIB() - sobel边缘检测运算 // PrewittDIB() - prewitt边缘检测运算 // KirschDIB() - kirsch边缘检测运算 // GaussDIB() - gauss边缘检测运算 // HoughDIB() - 利用Hough变换检测平行直线 // ContourDIB() - 轮廓提取 // Trace
EdgeContour
- 用于做遥感图像的边缘检测，使用Houff变换，轮廓提取和轮廓跟踪 等-Used to do remote sensing image edge detection, the use of Houff transform, contour extraction and contour tracking
Direct
- 用于图像边缘检测与轮廓处理，种子填充，hough变换-For image edge detection and contour processing, seed filling, hough transform
Yuzhifenge
- 图像阈值分割，包括：直方图门限选择、半阈值选择和迭代阈值。图像边缘提取，包括：轮廓提取、边界跟踪和区域增长-Image threshold segmentation, including: histogram threshold selection, quasi-threshold selection and iterative thresholds. Image Edge Detection, including: contour extraction, boundary tracking a
chap07
- 第七讲 边沿检测与提取，轮廓跟踪 共11张图-Seventh-speaking edge detection and extraction, contour tracing a total of 11 plans
chap_05
- 图像分割、边缘检测、轮廓跟踪与提取、图像匹配等源码-Image segmentation, edge detection, contour tracking and extraction, image matching, such as source
EdgeContour
- 图像边缘检测，提取及轮廓跟踪. VC++6实现.-Image edge detection, contour extraction and tracking. VC++ 6 to achieve.
The_digital_image_processing
- 数字图像处理算法的实现 包括：Hough变换，边缘检测，差影法，轮廓提取与跟踪投影法，图像复原，阈值分割，种子填充-Digital image processing algorithm, including: Hough transform, edge detection, and poor shadow law, contour extraction and tracking projection, image recovery, threshold segmentation, seed
EdgeContour
- 利用计算机进行图像边缘检测、提取和轮廓跟踪，算法简单，效率高-Using computer image edge detection, contour extraction and tracking algorithm is simple, efficient