Join Barron Stone for an in-depth discussion in this video Outlining the concepts, part of Code Clinic: Python (2014).
In this video I’ll explain the concepts…behind my image analysis routine.…I’ll describe the techniques I used,…and my reasons for doing things the way I did.…At the heart of my program is a function…called match template which I imported…from the scikit-image python toolkit.…The match template function takes a small…template image and finds where it occurs,…or most closely resembles another larger image.…It accomplishes this through a process…called normalized cross-correlation.…Cross-correlation is a standard method…for calculating how closely two series or values…are correlated or resemble each other,…and it’s commonly used for pattern recognition.…
In the case of an image which is represented…as a two dimensional array of pixels,…cross-correlation is performed by sliding…the template image across the larger search image.…At each location the algorithm calculates an integral…to determine how closely the template image…correlates with that section of the search image.…The match template function also normalizes…
Barron introduce challenges and provides an overview of his solutions in Python. Challenges include topics such as statistical analysis, searching directories for images, and accessing peripheral devices.
Visit other courses in the series to see how to solve the exact same challenges in languages like C#, C++, Java, PHP, and Ruby.
Skill Level Intermediate
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