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Description: 一种比较好用的边缘检测方法CORNER Find corners in tensity image.
％ CORNER works by the following step:
％ 1. Apply the Canny edge detector to the gray level image and obtain a
％ binary edge-map.
％ 2. Extract the edge contours from the edge-map, fill the gaps in the
％ contours.
％ 3. Compute curvature at a low scale for each contour to retain all
％ true corners.
％ 4. All of the curvature local maxima are considered as corner
％ candidates, then rounded corners and false corners due to boundary
％ noise and details were eliminated.
％ 5. End points of line mode curve were added as corner, if they are not
％ close to the above detected corners.
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Size: 79363 |
Author: 林蛋大 |
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Description: 一种比较好用的边缘检测方法CORNER Find corners in tensity image.
％ CORNER works by the following step:
％ 1. Apply the Canny edge detector to the gray level image and obtain a
％ binary edge-map.
％ 2. Extract the edge contours from the edge-map, fill the gaps in the
％ contours.
％ 3. Compute curvature at a low scale for each contour to retain all
％ true corners.
％ 4. All of the curvature local maxima are considered as corner
％ candidates, then rounded corners and false corners due to boundary
％ noise and details were eliminated.
％ 5. End points of line mode curve were added as corner, if they are not
％ close to the above detected corners.-A more useful edge detection method CORNER Find corners in tensity image. CORNER works by the following step: 1. Apply the Canny edge detector to the gray level image and obtain a binary edge-map. 2. Extract the edge contours from the edge-map, fill the gaps in the contours. 3. Compute curvature at a low scale for each contour to retain all true corners. 4. All of the curvature local maxima are considered as corner candidates, then rounded corners and false corners due to boundary noise and details were eliminated. 5. End points of line mode curve were added as corner, if they are not close to the above detected corners.
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Size: 78848 |
Author: 林蛋大 |
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Description: Source code to find area of contours.
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Size: 4096 |
Author: sid |
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Description: This paper provides an algorithm for partitioning grayscale images into disjoint regions of coherent
brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour and
texture differences are exploited simultaneously. Contours are treated in the intervening contour framework, while
texture is analyzed using textons. Each of these cues has a domain of applicability, so to facilitate cue combination we
introduce a gating operator based on the texturedness of the neighborhood at a pixel. Having obtained a local measure
of how likely two nearby pixels are to belong to the same region, we use the spectral graph theoretic framework of
normalized cuts to find partitions of the image into regions of coherent texture and brightness. Experimental results
on a wide range of images are shown.
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Size: 159744 |
Author: aan |
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Description: find contours in image using OpenCV
each contour s pixels are stored in a
sequence(CvSeq)
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Size: 2501632 |
Author: Jason |
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Description: 寻找所有轮廓.绘制所有轮廓并用椭圆拟合.
拟合当前轮廓.-Find all the contours. Draw all the outlines and fit with the ellipse. Fit the current profile.
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Size: 2048 |
Author: chengguo |
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Description: snake code for segmentation of images based on active contours.this code can help to find different spots in medical images for helping to diagnose various disease.
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Size: 3072 |
Author: mohammad |
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Description: 用snake方法 找出图像中物体的轮廓-Snake method to find the image with the contours of objects
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Size: 3207168 |
Author: 夏杰 |
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Description: OPENCV轮廓检索源代码,实现找到图像中的轮廓和画出轮廓-OpenCV source code find contours and draw contours
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Size: 1024 |
Author: 海蓝 |
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Description: Step 1: 二值化一幅图像，结果存为binary.bmp Step 2: 用不同彩色填充连通域（连通分量），结果存为connect.bmp Step 3: 在二值图像中找出轮廓并存储为countour.bmp-Step 1: The binary image of the results are saved as binary.bmp Step 2: fill with a different color connected domain (connected component), and results are saved as connect.bmp Step 3: In the binary image to find contours and store countour.bmp
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Size: 665600 |
Author: EARNER |
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Description: 此算法描写了怎样根据图片的灰度值来找边界，以及在什么条件下可以作为图像轮廓。-This algorithm describes how to find the gray value according to the picture border, and under what conditions can be used as image contours.
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Size: 2048 |
Author: 屈健健 |
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Description: 在图片中找出轮廓，并标记出来。在opencv中应该用在图片检测上-Find out the outline of the picture, and marked out. Should be used in the picture detection in opencv
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Size: 1024 |
Author: z |
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Description: OPENCV，提取轮廓程序示例，包括画轮廓和查找轮廓。-OPENCV, to extract contours procedures example, including painting the outline and contour Find.
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Size: 144384 |
Author: 李俊杰 |
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Description: 首先，请检查/样品在你的OpenCV的分布/ C/ squares.c的。这个例子提供了一个方形的检测，如何检测角落类似的功能，它应该是一个不错的开始。然后，一起来看看在OpenCV的功能，导向功能，如cvCornerHarris（）和cvGoodFeaturesToTrack（）。
上述方法可以返回许多角落类似的功能 - 最不会“真正的角落”你正在寻找。在我的应用程序，我只好检测，旋转或倾斜的广场（透视）。我的检测流水线包括：
从RGB转换为灰度级（cvCvtColor）
平滑（cvSmooth）
阈值（cvThreshold）
检测边缘（cvCanny）
查找轮廓（cvFindContours的）
线性特征的大致轮廓与（cvApproxPoly）
查找“矩形”，这是结构：已经拥有4个点的polygonalized轮廓，有足够的面积，相邻的边〜 90度，“对面的”顶点之间的距离足够大，等等。
第7步是必要的，因为稍微嘈杂的图像可以产生许多结构出现矩形后polygonalization。在我的应用程序中，我也有处理方状结构，内出现，或重叠所需的平方。我发现轮廓的区域属性和重心是有帮助的挑剔适当的矩形。-First, check out /samples/c/squares.c in your OpenCV distribution. This example provides a square detector, and it should be a pretty good start on how to detect corner-like features. Then, take a look at OpenCV s feature-oriented functions like cvCornerHarris() and cvGoodFeaturesToTrack().
The above methods can return many corner-like features- most will not be the "true corners" you are looking for. In my application, I had to detect squares that had been rotated or skewed (due to perspective). My detection pipeline consisted of:
Convert from RGB to grayscale (cvCvtColor)
Smooth (cvSmooth)
Threshold (cvThreshold)
Detect edges (cvCanny)
Find contours (cvFindContours)
Approximate contours with linear features (cvApproxPoly)
Find "rectangles" which were structures that: had polygonalized contours possessing 4 points, were of sufficient area, had adjacent edges were ~90 degrees, had distance between "opposite" vertices was of sufficient size, etc.
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Size: 1024 |
Author: clark |
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Description: opencv轮廓的简单应用：
相关函数如下：
cvFindContours，cvThreshold，cvContourArea，cvArcLength，cvBoundingRect，cvMinAreaRect2，cvBoxPoints，cvMinEnclosingCircle，cvDrawContours。
1.查找轮廓
2.按地址依次取出轮廓
3.计算轮廓的相关参数
4、根据实际需求做取舍，画出轮廓-opencv silhouette simple application:
Correlation function as follows:
cvFindContours, cvThreshold, cvContourArea, cvArcLength, cvBoundingRect, cvMinAreaRect2, cvBoxPoints, cvMinEnclosingCircle, cvDrawContours.
1 Find contours
(2) Remove the outline followed by address
3 outlines the relevant parameters calculated
4, make a choice based on actual demand, draw the outline
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Size: 744448 |
Author: 查改琴 |
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Description: 寻找并绘制图像的轮廓,最终显示寻找到的轮廓个数，及轮廓图。-Find and draw the outline of the image, the final display to find the number of contours, and contour.
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Size: 2360320 |
Author: zhizhuo_33 |
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Description: 基于最小二乘法的直线拟合，链表成员是浮点型的点-it can be used to fitting line in opencv after find contours,the list member is PointF
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Size: 1024 |
Author: 新村 |
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Description: VS2013+OPENCV2.4，阀值分割，查找轮廓，显示缺陷，可知程序运行时间-VS2013+OPENCV2.4, threshold segmentation, find contours, display defects, known program run time
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Size: 7636992 |
Author: 幻影之武 |
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Description: Gradient Vector Flow (GVF) snake is one kind of active contours - curves that can move within images to find the boundaries of objects. 3D active contours are also known as deformable models. GVF snake begins with calculating the GVF force field over the image domain, which will force the snake into concave regions of original images. Since the calculation of GVF force field usually takes a long time, in this project we implement the GVF algorithm with GPU, which will accelerate the algorithm to a great extent.
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Size: 232448 |
Author: jeffsantana
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