- DIP - Computer Vision and Graphics
- DIP - Optical Character Recognition
- DIP - JPEG compression
- DIP - Introduction to Color Spaces
- DIP - High Pass vs Low Pass Filters
- DIP - Convolution theorm
- DIP - Fourier series and Transform
- DIP - Frequency Domain Analysis
- DIP - Laplacian Operator
- DIP - Krisch Compass Mask
- DIP - Robinson Compass Mask
- DIP - Sobel operator
- DIP - Prewitt Operator
- DIP - Concept of Edge Detection
- DIP - Concept of Blurring
- DIP - Concept of Masks
- DIP - Concept of convolution
- DIP - Gray Level Transformations
- DIP - Histogram Equalization
- DIP - Introduction to Probability
- DIP - Histogram Stretching
- DIP - Histogram Sliding
- DIP - Image Transformations
- DIP - Brightness and Contrast
- DIP - Histograms Introduction
- DIP - Concept of Dithering
- DIP - ISO Preference curves
- DIP - Concept of Quantization
- DIP - Gray Level Resolution
- DIP - Pixels Dots and Lines per inch
- DIP - Spatial Resolution
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- DIP - Concept of Zooming
- DIP - Pixel Resolution
- DIP - Concept of Sampling
- DIP - Grayscale to RGB Conversion
- DIP - Color Codes Conversion
- DIP - Types of Images
- DIP - Concept of Bits Per Pixel
- DIP - Perspective Transformation
- DIP - Concept of Pixel
- DIP - Camera Mechanism
- DIP - Image Formation on Camera
- DIP - Concept of Dimensions
- DIP - Applications and Usage
- DIP - History of Photography
- DIP - Signal and System Introduction
- DIP - Image Processing Introduction
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Krisch Compass Mask
Kirsch Compass Mask is also a derivative mask which is used for finding edges. This is also pke Robinson compass find edges in all the eight directions of a compass. The only difference between Robinson and kirsch compass masks is that in Kirsch we have a standard mask but in Kirsch we change the mask according to our own requirements.
With the help of Kirsch Compass Masks we can find edges in the following eight directions.
North
North West
West
South West
South
South East
East
North East
We take a standard mask which follows all the properties of a derivative mask and then rotate it to find the edges.
For example let’s see the following mask which is in North Direction and then rotate it to make all the direction masks.
North Direction Mask
-3 | -3 | 5 |
-3 | 0 | 5 |
-3 | -3 | 5 |
North West Direction Mask
-3 | 5 | 5 |
-3 | 0 | 5 |
-3 | -3 | -3 |
West Direction Mask
5 | 5 | 5 |
-3 | 0 | -3 |
-3 | -3 | -3 |
South West Direction Mask
5 | 5 | -3 |
5 | 0 | -3 |
-3 | -3 | -3 |
South Direction Mask
5 | -3 | -3 |
5 | 0 | -3 |
5 | -3 | -3 |
South East Direction Mask
-3 | -3 | -3 |
5 | 0 | -3 |
5 | 5 | -3 |
East Direction Mask
-3 | -3 | -3 |
-3 | 0 | -3 |
5 | 5 | 5 |
North East Direction Mask
-3 | -3 | -3 |
-3 | 0 | 5 |
-3 | 5 | 5 |
As you can see that all the directions are covered and each mask will give you the edges of its own direction. Now to help you better understand the concept of these masks we will apply it on a real image. Suppose we have a sample picture from which we have to find all the edges. Here is our sample picture:
Sample Picture
![Kirsch Compass Mask](/dip/images/kirsch1.jpg)
Now we will apply all the above filters on this image and we get the following result.
North Direction Edges
![Kirsch Compass Mask](/dip/images/kirsch2.jpg)
North West Direction Edges
![Kirsch Compass Mask](/dip/images/kirsch3.jpg)
West Direction Edges
![Kirsch Compass Mask](/dip/images/kirsch4.jpg)
South West Direction Edges
![Kirsch Compass Mask](/dip/images/kirsch5.jpg)
South Direction Edges
![Kirsch Compass Mask](/dip/images/kirsch6.jpg)
South East Direction Edges
![Kirsch Compass Mask](/dip/images/kirsch7.jpg)
East Direction Edges
![Kirsch Compass Mask](/dip/images/kirsch8.jpg)
North East Direction Edges
![Kirsch Compass Mask](/dip/images/kirsch9.jpg)
As you can see that by applying all the above masks you will get edges in all the direction. Result is also depends on the image. Suppose there is an image, which do not have any North East direction edges so then that mask will be ineffective.
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