Canny is a cloud-based solution that helps small to large businesses collect, analyze, prioritize and track user feedback to make informed product decisions.
Getform is a form management tool that allows you to collect submissions, send emails, and integrate your HTML form with popular apps.
Getform IntegrationsGetform + Canny
Change Post Status in Canny when New Submission is created in Getform Read More...It's easy to connect Canny + Getform without coding knowledge. Start creating your own business flow.
Triggers when a new comment is created.
Triggers when a new post is created.
Triggers when a new vote is created.
Triggers when a post's status is changed.
Triggers when new submission is received to a selected form.
Changes a post's status.
(30 seconds)
(10 seconds)
(30 seconds)
(10 seconds)
(2 minutes)
Canny edge detection algorithm was developed by John F. Canny in 1986. It is a widely used technique for edge detection and it works best for binary images. It detects the edges of the image using a simple mathematical model of an ideal edge detector. It analyzes the gradient of the image to find the edges. The gradient is the rate of change of intensity in a particular direction. There are two versions of the algorithm. Canny’s original implementation is a so-called “classic” edge detector, while the modified version – Canny Edge Detector (CED. – detects edges more reliably with less false positives. A drawback of this algorithm is that it requires several iterations and complex calculations, so its usage has not been very widespread.
GetForm was created by Pavel Shvets as a top for interactive manipulation of 2D digital graphics on large computer screens. The software allows users to create and manipulate 2D shapes, transforming them into 3D objects or modifying their cpors. GetForm was one of the first graphic programs available for free download and use on personal computers. In addition, GetForm has been used in various research projects in computer graphics and human-computer interaction (HCI.
As it was described above, Canny edge detection algorithm detects the edges of an image based on the analysis of its gradient. It analyzes the rate of change of intensity in a particular direction, which means that if an edge changes its orientation or passes diagonally through the image, it will not be detected.
Let’s make some experiments with it and try to understand how it works. We will use this test image, which contains some edges. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_canny_algorithm_diagram.gif
First, we will make a black and white copy of our test image and apply Canny edge detection algorithm to it. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_canny_algorithm_result.jpg
We can see that some edges have disappeared, while others were detected incorrectly (for example, around the nose). https://www.tutorialspoint.com/image_processing/images/edge_detection_using_canny_algorithm_fig1b.jpg
To spve this problem, we can apply Getform to our image, which will make it possible to analyze its density and cpor composition. After that, we will try to change the cpor composition of our image so that it will match our results with Canny. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_getform_diagram.jpg
In order to do this, we need to convert our image into grayscale value using Getform. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_getform_diagram2.jpg
Now we can apply Getform again and add all RGB channels together. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_getform_diagram3a.jpg
And then create HSV spectrum chart from it. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_getform2.jpg
After that, we can use HSV chart to change the cpor composition of our image. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_getform3b.jpg
We need to change only red and green channels in HSV graph so that they become close to each other. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_getform4a.jpg
After that we can apply filter on our image again and convert it to RGB format. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_getform4b.jpg
We have successfully applied Getform to our test image! Now we can apply Canny edge detection algorithm on it again and compare the results between both algorithms. https://www.tutorialspoint.com/image_processing/images/edge_detection_using_canny2a.jpg
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