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- 投影矫正，去十字网格滤波，膨胀腐蚀形态学处理-Projection correction, to cross the grid filter, expansion of corrosion morphology
css
- 基于形态学的边缘提取方法，而由曲率尺度空间提取角点的文章-Edge extraction method based on morphology while extracting corner points by the curvature scale space article
MM
- 根据数学形态学原理编写的信号去噪程序，简单易懂，适合初学者-According to the principle of mathematical morphology write signal denoising procedures, easy to understand for beginners
BPN-based-iris-Recongition
- method for automatic blood vessel detection based on mathematical morphology and coye filter. The proposed method performs certain preprocessing steps on the gray-scale of the input image to enhance image quality. The blood vessels are highlighted us
matlab
- 输入一幅图像，用传统的算子方法进行检测与用形态学腐蚀之后使原图像与腐蚀后的图像相减得到图像边缘进行比较-The Mathematical Morphology Image Edge Detection Based on MATLAB
palm
- 形态学中的腐蚀和膨胀运算。首先，对图像进行低通滤波，消除细小噪声的干扰。 在滤波时，没有采用传统的中值滤波器，而是采用顺序统计滤波器ordfilt2-Erosion and dilation operation in morphology. Firstly, the image is filtered by low pass filtering to eliminate the interference of small noise. In filtering, the traditi
MathematicalMorphology2d
- 数学形态学，二维示例程序，包括图像的腐蚀与膨胀操作-Morphology, two-dimensional sample programs, including image corrosion and expansion of operations
Endothelial_IABEM2014.tar
- Investigating the Effect of the Morphology and Distribution of Endothelial Cells on Flow Transport in Blood Vessels using Fast BEM. The slides presented in the International Association for Boundary Element Method, August 2014.
split_4
- 本方法首先利用数学形态学分水岭算法对图像进行分割,然后对分割后的图像进行相似区域合并,以减少分水岭方法产生的过分割现象-This method first USES mathematical morphology watershed algorithm for image segmentation, and similar to the image after segmentation region merging, in order to reduce the over-segmentatio
Morphological-image-processing
- 1. 膨胀的简单应用、使用 strel 函数、腐蚀的说明 2. 函数 imopen 和 imclose 的应用、使用 IPT 函数 bwhitmiss 3. 灰度图像形态学开运算和闭运算 4. 灰度图像形态学使用重构删除复杂图像的背景-1. The expansion of the simple application, use the strel function, corrosion 2. Imopen function and application, use the IP
morphology
- 形态学实现代码，腐蚀，膨胀，开运算，闭运算等-Morphological implementation code, erosion, dilation, opening operation and closing operation, etc.
mathematical_morphology_1d
- 自己编写的一维数学形态学滤波示例程序，可以直接运行-One dimensional mathematical morphology filtering procedures, can be directly run
circles
- 对图片提出一种基于形态学的完全自动化方法，判定哪些黑色点是背景点哪些点包括在球体之中（也就是黑色区域完全包括在白色区域内）。-The picture presented fully automated method based on morphology, to determine which is the black dot background point which points are included in the sphere among the (black region is f
dustremover
- 祛除灰尘的例程，用边缘检测和中值滤波检测灰尘，用二值形态学修饰灰尘。适用于显微镜灰度图像。-Remove dust routines, with edge detection and median filtering to detect dust, dust with binary morphology modification. Suitable for microscopic grayscale images.
Weightbased-adaptive-image
- 基于形态学的权重自适应图像去噪；通过串并联的滤波降噪对比图，说明并联降噪的优越性-Heavy adaptive image denoising based on morphology right noise filtering by series-parallel comparison chart, show the advantages of parallel noise reduction
protection
- 两篇SCI论文，分别介绍基于形态奇异熵、高阶统计量的输电线路继电保护新方法 涉及形态学、奇异值分解、熵、高阶统计量等算法。-Two SCI-indexed papers respectively introduce two novel transmission line protection methods based on morphology singular entropy and high order statistics. Algorithms relates to morph
xingtaixue
- 基于自适应多尺度数学形态学的信号去噪，程序可以直接运行。-signal denoising based on adaptive multi-scale mathematical morphology
Multifocus-Image-Fusion
- Ishita De a, Bhabatosh Chanda的论文Multi-focus image fusion using a morphology-based focus measure in a quad-tree structure，实现多图像的融合-Ishita De a, Bhabatosh Chanda paper Multi-focus image fusion using a morphology-based focus measure in a quad-tree struc
Erosion
- Morphology: Erosion - Erosion is one of two fundamental operations (the other being dilation) in morphological image processing which all other morphological operations are based. It was originally defined for binary images, later being extended to g
morpho
- 利用VS2010和opencv2.4.8写的图像形态学处理的程序，包括利用形态学的方法检测图像角点-Use the program written in VS2010 and opencv2.4.8 image morphology processing, including the use of morphological methods for detecting image corners