Digital Image processing techniques have been around the world since the advent of computers. Theses techniques have been used for various uses like removing a simple blemish from your photo to track down an enemy jet from a military radar. Of the course of time there are various digital image processing techniques have been developed to remove more and more data from an existing image.
Image processing techniques can be widely classified into 2 categories :
- Spatial Domain
- Frequency Domain
Spatial Domain Image processing consists of various techniques of altering the image by looking into each individual pixel of the image
Frequency Domain Image processing consists of various techniques of altering the image by looking into the amount of variation in the pixel (frequency) of the the image
Today Image processing techniques have found a new domain of use case 'Machine Learning' . These Techniques can be used to extract the features of an image thereby increasing the accuracy and reducing the time of training required. And yes, you can still use these techniques to give a non machine learning solution to a given problem statement
Project Photolab is a compilation of 5 different classes of Image processing techniques starting from simple black and white operations to edge detection techniques along with a few noise removal and reduction techniques .
Check out here on https://github.com/bvks2020sameer/Photolab
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