Description: 极大值抑制与双阈值门限得到图像边缘：
* nonmaxsuppts.m Code for performing non-maxima suppression and thresholding of points generated by a feature/corner detector. It optionally returns sub-pixel feature locations.-Maxima suppression and dual-threshold threshold obtained Edge:* nonmaxsuppts.m Code for performing non-maxima suppression and thresholding of points generated by a feature/corner detector. It optionally returns sub-pixel feature locations. Platform: |
Size: 2048 |
Author:asdasdasd |
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Description: Non maxima suppression and thresholding for points generated by a feature
or corner detector. Platform: |
Size: 2048 |
Author:mahmoud |
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Description: nonmaxsup——非最大值抑制
hysthresh——设定阈值区间，返回一个二值化图像
canny——边缘探测，图像边缘增强
adjgamma——调整图像的伽马值
findline——利用线性Hough变换和Canny边缘探测得到的线上各点的坐标
circlecoords——返回由圆的半径和圆心坐标决定的圆上各点像素的坐标
houghcircle——取一幅经过canny变换的图像，利用hough变换找到图像中的一个圆
findcircle——计算所得线上各点的坐标归纳出一个圆的半径和圆心，确定该圆的各点坐标
gaborconvolve——利用一维盖伯滤波器对图像进行处理
gethammingdistance ——返回两幅虹膜图像提取的特征码之间的海明距离
linecoords——返回一条线的上各点的x,y坐标值-nonmaxsup- non-maximum suppression hysthresh- set the threshold range, returns a binary image canny- edge detection, image edge enhancement adjgamma- adjust the image' s gamma value findline- linear Hough transform and Canny edge detection get the coordinates of each point circlecoords online- Returns coordinate houghcircle on the circle of the radius and center coordinates of the points decision pixels- After taking a picture canny transformation, using hough transform to find the image of a circle findcircle- the calculated coordinates of each point line summed up a circle of radius and center, to determine the coordinates of each point of the circle gaborconvolve- using a 维盖伯 filter for image processing gethammingdistance- returns two iris images extracted linecoords Hamming distance between the signature- a return line to the points on the x, y coordinate values Platform: |
Size: 4573184 |
Author:廖志伟 |
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Description: 利用canny边缘检测检测图片边缘，实现图像分割。其中非极大抑制采用的是传统方式。-Using Canny edge detection of image edge detection, image segmentation. The non maximum suppression is used in the traditional way. Platform: |
Size: 174080 |
Author:马凌风 |
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Description: Gray Level Edge Thinning Method
Abstract. An effective edge thinning algorithm is important in image segmentation and object identification since it increases the possibility of success in detecting objects in the image and saves the processing time in the further steps such as labeling and image transformation. We investigate some gray level edge thinning method that is based on the gradient magnitude within 3x3 local neighborhood. The new method has been tested with various types of images the real world. Experimental results show that this method produces more accurate images than those of the popular non-maximum suppression methods do.
-Gray Level Edge Thinning Method
Abstract. An effective edge thinning algorithm is important in image segmentation and object identification since it increases the possibility of success in detecting objects in the image and saves the processing time in the further steps such as labeling and image transformation. We investigate some gray level edge thinning method that is based on the gradient magnitude within 3x3 local neighborhood. The new method has been tested with various types of images the real world. Experimental results show that this method produces more accurate images than those of the popular non-maximum suppression methods do.
Platform: |
Size: 120832 |
Author:mohammed |
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Description: 根据CNNAY算法的4个步骤
1. 用高斯滤波器平滑图像；（图像去噪）
2. 用一阶偏导有限差分计算梯度幅值和方向；（特征增强）
3. 对梯度幅值进行非极大值抑制 ；（边缘检测）
4. 用双阈值算法检测和连接边缘。（形态学处理）
编写的边缘检测程序，简单实用(There are four parts of Canny edge detection:
1. smoothing the image with Gauss filter; (image denoising)
2. calculate gradient amplitude and direction by first order partial derivative finite difference method (feature enhancement)
3. non maximum suppression of the gradient amplitude; (edge detection)
4. detect and connect edges with double threshold algorithm. (morphological treatment)) Platform: |
Size: 1024 |
Author:UJSLEMON
|
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Search - Non-maximum suppression