Building Computer Vision Applications with Python | The Basics of Image Processing | Part 2
Image processing is a ubiquitous technology these days, used in just about every feature of smartphone cameras, in video games, social media apps, graphics software, and much more. Computer vision is the field of science that makes it possible for computers to not just capture images, but to process, analyze, and understand digital images. In this course, Eduardo Corpeño shows you how to use Python to write image processing operations of your own from scratch, to get a deeper understanding of the under-the-hood operations of image processing and popular tools like OpenCV. Eduardo shows you how to tap into the details of the algorithms behind image processing so you can understand what’s going on inside and make better use of these tools in the future. He also provides programming challenges so you can create your own implementations and compare your work with his solutions.
Introduction
Computer vision under the hood
What you should know
Using the exercise files
4. Filters
Convolution filters
Average filters
Median filters
Gaussian filters
Edge detection filters
Challenge: Convolution filters
Solution: Convolution filters
5. Image Scaling
Image downscaling methods
Downscaling example
Image upscaling methods
Upscaling example
Challenge: Resize a picture
Solution: Resize a picture
6. Fun with Cuts
Image cuts
Stitching two images together
Cuts in panoramic photography
Challenge: Stitch two pictures together
Solution: Stitch two pictures together
7. Morphological Modifications
Why modify objects?
Erosion and dilation
Open and close
Challenge: Help a robot
Solution: Help a robot
Conclusion
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