cannycv
Detects edges of an image handle with the Canny algorithm.
Syntax
R = cannycv(handle, threshold1, threshold2...)
R = cannycv(handle, threshold1, threshold2, size, gradient)
Inputs
- handle
- Handle of a single channel gray scale image.
- threshold1
- Lower edge detection threshold.
- threshold2
- Upper edge detection threshold.
- size
- Optional aperture size for the Sobel operator. Default value is 3
- gradient
- Optional flag for gradient. Default value is false, indicating that default gradient will be used.
Outputs
- R
- Handle of the output image.
Example
Detect the edges with the Canny algorithm:
Figure 1. Input image
Figure 2. Output image
handle = imreadcv('bird3.jpg', 0);
R = cannycv(handle, 50, 100);Figure 1. Input image
Figure 2. Output image
Detect the edges and dilate the output:
Figure 3. Input image
Figure 4. Output image
imgoriginal = imreadcv('Dog.jpg',1);
figure(1);
imshowcv(imgoriginal);
%Conver the image to gray scale
img = cvtcolorcv(imgoriginal, 6);
edges = cannycv(img, 70, 180);
dilatededges = dilatecv(edges, []);
figure(2);
imshowcv(erodededges);Figure 3. Input image
Figure 4. Output image