Description: 我们给出一个模板 和一幅图象 。不难发现原图中左边暗，右边亮，中间存在着一条明显的边界。进行模板操作后的结果如下： 。
可以看出，第3、4列比其他列的灰度值高很多，人眼观察时，就能发现一条很明显的亮边，其它区域都很暗，这样就起到了边沿检测的作用。
为什么会这样呢？仔细看看那个模板就明白了，它的意思是将右邻点的灰度值减左邻点的灰度值作为该点的灰度值。在灰度相近的区域内，这么做的结果使得该点的灰度值接近于0；而在边界附近，灰度值有明显的跳变，这么做的结果使得该点的灰度值很大，这样就出现了上面的结果。
这种模板就是一种边沿检测器，它在数学上的涵义是一种基于梯度的滤波器，又称边沿算子，你没有必要知道梯度的确切涵义，只要有这个概念就可以了。梯度是有方向的，和边沿的方向总是正交(垂直)的，例如，对于上面那幅图象的转置图象，边是水平方向的，我们可以用梯度是垂直方向的模板 检测它的边沿。
例如，一个梯度为45度方向模板 ，可以检测出135度方向的边沿。-we give a template and an image. It is not difficult to find the maximum were left dark, right-liang, in the middle there is a clear boundary. After the template for the operation results are as follows :. Can be seen, three, four out other than the gray value is much higher, eye observation, we can obviously found a bright side. Other regions are dark, and this has played a role in the detection of 2500. Why is this the case? A closer look at the template on which to understand it. It means the right to the point o gray minus left point as a gray value of the point of gray values. In a similar gray area, do so as a result of the point of gray values close to 0; And near the border. gray values jump significantly changed, the results do make the point very gray value, and this appeared to Platform: |
Size: 9216 |
Author:李涯 |
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Description: 本源码是基于视频检索的镜头边界检测，能有效的检测渐变与突变。对于初涉该领域的人应该会有很大的帮助！-the source video retrieval is based on the shot boundary detection, the effective evolution and mutation detection. For a fledgling in the field should be of great help! Platform: |
Size: 422912 |
Author:张小军 |
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Description: 利用霍夫变换来实现图像的边界检测，本代码实现圆和直线的检测-use Hough transform to image the boundary detection, the moon and the code to achieve a linear detection Platform: |
Size: 30720 |
Author:liuwei |
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Description: 可以用来实现对物体的边界检测追踪,包含UIR,H,C,PRJ文件-Can be used to achieve the object boundary detection tracking, including the UIR, H, C, PRJ file Platform: |
Size: 7168 |
Author:陈英 |
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Description: 这是一种关于镜头边界检测的程序，是在基于信息熵的基础上完成的！-This is a shot boundary detection on the procedure is based on information entropy based on the completed! Platform: |
Size: 4157440 |
Author:jiangwei |
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Description: 基于mpeg2视频留的实时的镜头边界检测算法描述-Mpeg2 to stay based on the real-time video shot boundary detection algorithm described in Platform: |
Size: 904192 |
Author:zhangnan |
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Description: 自己做的关于边缘检测与边界跟踪的matlab程序-Own on the edge of the boundary detection and tracking procedures matlab Platform: |
Size: 112640 |
Author:wang |
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Description: This a grayscale boundary detection using OpenCV-This is a grayscale boundary detection using OpenCV Platform: |
Size: 479232 |
Author:Afra |
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Description: i have attached code for boundary detection,
face rcognition
gradient calcul ation
color spaces Platform: |
Size: 166912 |
Author:pooja |
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Description: Shot boundary detection is always an important topic in
digital video processing. It is the first important task of
content-based video retrieval and indexing. In this paper, a
new shot boundary detection algorithm is proposed, based on
Particle Swarm Optimization Classifier. This method firstly
takes the difference curves of U-component histograms as the
characteristics of the differences between video frames, and
then utilizes a Slide-Window Mean Filter to filter difference
curves and a KNN Classifier applying PSO to detect and
classify the shot transitions. This method has three advantages
that it is more sensitive to gradual transitions each curve
graphic with remarkable characteristics corresponds to a shot
transition Cuts and Gradual transitions could be detected in a
same step. As experiments shown, the performance of this
method is superior to the traditional shot boundary detection
methods, and this method can achieve high recall and
precision rate.-Shot boundary detection is always an important topic in
digital video processing. It is the first important task of
content-based video retrieval and indexing. In this paper, a
new shot boundary detection algorithm is proposed, based on
Particle Swarm Optimization Classifier. This method firstly
takes the difference curves of U-component histograms as the
characteristics of the differences between video frames, and
then utilizes a Slide-Window Mean Filter to filter difference
curves and a KNN Classifier applying PSO to detect and
classify the shot transitions. This method has three advantages
that it is more sensitive to gradual transitions each curve
graphic with remarkable characteristics corresponds to a shot
transition Cuts and Gradual transitions could be detected in a
same step. As experiments shown, the performance of this
method is superior to the traditional shot boundary detection
methods, and this method can achieve high recall and
precision rate. Platform: |
Size: 395264 |
Author:saeed |
Hits:
Search - boundary detection