January 2020
Intermediate to advanced
346 pages
9h 8m
English
In this chapter, we are going to experiment with one of the most popular ways genetic algorithms have been applied to image processing – the reconstruction of an image with a set of semi-transparent polygons. Along the way, we will gain useful experience in image processing, coupled with a visual insight into the evolutionary process.
We will start with an overview of image processing in Python and get acquainted with three useful libraries – Pillow, scikit-image, and opencv-python. Then, we will find out how an image can be drawn from scratch using polygons and how the difference between two images can be calculated. Next, we will develop a genetic algorithm-based program to reconstruct a segment of a famous ...
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