Description: 针对多椭圆检测问题提出了一种快速随机检测算法。该算法利用在图像中随机采样到的一个边缘点和
局部搜索到的两个边缘点以及这三个点的邻域信息确定候选椭圆,再将候选椭圆变换为对应圆,通过确认真圆来确
认真椭圆。在确定候选椭圆时,最大限度地减少随机采样点数‰ 剔除更多的非椭圆点,降低了无效采样,减少了无效
计算。数值实验结果表明:该算法具有良好的鲁棒性,其检测速度比同类算法快-Ellipse detection problem for many a fast random detection algorithm. The algorithm uses random sampling in the image of an edge point and the local search to the two edge points, as well as the three-point neighborhood information to determine the candidate ellipse, and then transformed into the corresponding elliptical candidate won, through the identification of real yen to confirm really elliptical. In determining when a candidate ellipse, to minimize random sampling points ‰ remove more non-oval points, reducing invalid sampling, to reduce the calculation invalid. Numerical experimental results show that: the algorithm has good robustness, and its detection faster than similar algorithms quickly Platform: |
Size: 526336 |
Author:刘镖峰 |
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Description: 用改进的随机Hough变换检测胸水图像中的细胞，模式识别中的图像处理-Using a Modified Hough Transform Detection of random images of cells in pleural fluid, pattern recognition in image processing Platform: |
Size: 221184 |
Author:张明伟 |
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Description: 椭圆检测拟合程序，能够从图片中自动提取椭圆并进行拟合
-Ellipse detection fitting procedure can be automatically extracted from the image to fit the ellipse and the Platform: |
Size: 1024 |
Author:licheng |
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Description: Hough变换是图像处理中从图像中识别几何形状的基本方法之一。Hough变换的基本原理在于利用点与线的对偶性，将原始图像空间的给定的曲线通过曲线表达形式变为参数空间的一个点。这样就把原始图像中给定曲线的检测问题转化为寻找参数空间中的峰值问题。也即把检测整体特性转化为检测局部特性。比如直线、椭圆、圆、弧线等。
-Hough transform image processing image recognition from the basic geometry of one of the methods. The basic principle of Hough transform is to use point and line duality, the original image space, the curve of a given expression through the curve into a parameter space of a point. This put the original image in the detection of a given curve is transformed into a parameter space to find problems in the peaks. That is to detect the overall characteristics of transformation for the detection of local features. For example a straight line, ellipse, circle, arc and so on. Platform: |
Size: 24576 |
Author:王超 |
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Description: 用边缘检测算法检测的圆的像的边缘点，并用多元线性回归求出椭圆的方程，然后按照我们的模型中提供的方法，求出每个圆心的像的位置-Using edge detection algorithm to detect the edge of the image circle points, and multiple linear regression equation of the ellipse obtained, and then follow the model provided by our method, find the location of each center of the circle as Platform: |
Size: 1024 |
Author:王帅哥 |
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Description: Edge detection result should be enhanced using linear method like Median filter to
remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the
centre of the pupil by counting the number of black pixels (zero value) of each column and
row. Then get each row and column that has the maximum number of these black pixels.
Then determine the center by simple calculation according to the image coordinate to set it
correct on the image, consequently we can determine the radius of the pupil. Thus we can find
the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to
locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms
of circle and ellipse. Platform: |
Size: 1024 |
Author:boss |
Hits:
Description: Edge detection result should be enhanced using linear method like Median filter to
remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the
centre of the pupil by counting the number of black pixels (zero value) of each column and
row. Then get each row and column that has the maximum number of these black pixels.
Then determine the center by simple calculation according to the image coordinate to set it
correct on the image, consequently we can determine the radius of the pupil. Thus we can find
the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to
locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms
of circle and ellipse. Platform: |
Size: 2048 |
Author:boss |
Hits:
Description: Edge detection result should be enhanced using linear method like Median filter to
remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the
centre of the pupil by counting the number of black pixels (zero value) of each column and
row. Then get each row and column that has the maximum number of these black pixels.
Then determine the center by simple calculation according to the image coordinate to set it
correct on the image, consequently we can determine the radius of the pupil. Thus we can find
the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to
locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms
of circle and ellipse. Platform: |
Size: 1024 |
Author:boss |
Hits:
Description: Edge detection result should be enhanced using linear method like Median filter to
remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the
centre of the pupil by counting the number of black pixels (zero value) of each column and
row. Then get each row and column that has the maximum number of these black pixels.
Then determine the center by simple calculation according to the image coordinate to set it
correct on the image, consequently we can determine the radius of the pupil. Thus we can find
the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to
locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms
of circle and ellipse. Platform: |
Size: 1024 |
Author:boss |
Hits:
Description: Edge detection result should be enhanced using linear method like Median filter to
remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the
centre of the pupil by counting the number of black pixels (zero value) of each column and
row. Then get each row and column that has the maximum number of these black pixels.
Then determine the center by simple calculation according to the image coordinate to set it
correct on the image, consequently we can determine the radius of the pupil. Thus we can find
the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to
locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms
of circle and ellipse. Platform: |
Size: 1024 |
Author:boss |
Hits:
Description: Edge detection result should be enhanced using linear method like Median filter to
remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the
centre of the pupil by counting the number of black pixels (zero value) of each column and
row. Then get each row and column that has the maximum number of these black pixels.
Then determine the center by simple calculation according to the image coordinate to set it
correct on the image, consequently we can determine the radius of the pupil. Thus we can find
the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to
locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms
of circle and ellipse. Platform: |
Size: 1024 |
Author:boss |
Hits:
Description: Edge detection result should be enhanced using linear method like Median filter to
remove the garbage around the pupil to gain clear pupil to determine perfect centre. Get the
centre of the pupil by counting the number of black pixels (zero value) of each column and
row. Then get each row and column that has the maximum number of these black pixels.
Then determine the center by simple calculation according to the image coordinate to set it
correct on the image, consequently we can determine the radius of the pupil. Thus we can find
the pupillary boundary (inner). A similar procedure is extended by using a coarse scale to
locate the outer boundary (limbus) which can be apparent by using the mid-point algorithms
of circle and ellipse. Platform: |
Size: 1024 |
Author:boss |
Hits:
Description: 基于霍夫变换的外形检测算法的实现，包括图像读取与显示、彩色图像转化为灰度图、灰度图二值化、膨胀腐蚀、图像轮廓提取、线性图形检测以及椭圆检测-Shape detection algorithm based on Hough transform implementation, including the image read and display color images into grayscale, grayscale binary and expansion corrosion image contour extraction, linear pattern detection and ellipse detection Platform: |
Size: 4959232 |
Author:chenxin |
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Description: 该函数用于图像中圆形的识别与类圆形的识别-this function is used to detect the circle and ellipse in the image Platform: |
Size: 2482176 |
Author:george |
Hits:
Search - ellipse detection image