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# Canny Edge detection using OpenCV and python
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## What is Canny Edge Detection?
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Canny Edge Detection
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It is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images.
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It was developed by John F. Canny ,an Australian computer scientist, back in 1986.
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### _The Canny edge detection algorithm is composed of 5 steps_:
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+ Noise reduction;
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+ Gradient calculation;
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+ Non-maximum suppression;
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+ Double threshold;
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+ Edge Tracking by Hysteresis.
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## Lets see how it's done.
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1. #### Input image:
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Input in RGB format.
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2. #### Converting the image to grayscale:
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For easier calculations.
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3. #### Smoothing the image:
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Smoothing of image for noise reduction. Gradient is the first order derivatives of image for each direction.
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It is cause of edges that seems more and the edges look thick.
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4. #### Image gradient:
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Gradient is the function of the partial derivatives. I applied to the image convolution process with Sobel filters to obtain this partial derivative.
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5. #### Non-maximum suppression:
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In this step the pixel is compared with its two neighbors of the pixel, if the compared pixel is larger than neighbor we do not change the pixel,
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otherwise, this pixel is not maximum value hence, we set the zero to that pixel.
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6. #### Tracking the edge by hysteresis:
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In this step we choose two type of threshold, high and low threshold value. Afterward, each pixel of image is compared with two different threshold value.
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If the pixel is larger than the high threshold, this pixel mark with 255 in the final image.
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If the pixel between high threshold and low threshold. If the pixel is smaller than low-threshold image, mark as black with 0 (black) value in the resulting image.
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7. #### Final Results:
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After passing all of the mentioned steps, we will give the final result from the method.
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# Output Results:
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For more detail on learning Canny Edge Detection and maths behind , see my article [here](https://medium.com/simply-dev/what-is-canny-edge-detection-cfefa272a8d0)
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