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The Fastest and best way to learn how to do computer image processing #piday #raspberrypi @Raspberry_Pi

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Via Network World

I’ve been fascinated bycomputer image processing for a long time and over the years I’ve thought of lots of uses for it but it’s always been so technical and required such an investment of time that I’ve never really got too deep into the technologies and techniques … until recently. I was reading something interesting about a famous free, open source image processing library called OpenCV and stumbled across Adrian Rosebrock’s FREE OpenCV crash course.

This course is outstanding! It’s a free 21 day program that takes you from the basics of setting up the software you need (Python, a load of Python libraries, and OpenCV), discusses the importance and applications of image processing, and then takes you all the way to building a simple image search engine. Amazing stuff.

What Rosebrock’s also doing with his course, beyond giving you a basic practical education in image processing, is selling you on his book, Practical Python and OpenCV + Case Studies. I got a hard copy of the book a few days ago and I’m really impressed. This book is a goldmine for beginners as well as intermediate computer vision engineers.

The book begins with some of the same background material as the email course including setting up all of the resources you’ll need but with the book you can also download Adrian’s virtual machine which combines all of the required tools with Ubuntu so you jump start your image processing education.The first part of the book covers the basics of loading, displaying, and saving images, the basics of images, using OpenCV for drawing, image processing (transformations, arithmetic, masking, color spaces, etc), computing histograms, smoothing and blurring images, thresholding, gradients and edge detection and contours.

The second part is where you get a taste for useful applications. It’s a collection of case studies that cover face detection, object tracking, eye tracking, handwriting recognition, plant classification, and how to build an Amazon book cover search engine.

Rosebrock’s writing style is great; he makes sure you understand key concepts, he doesn’t belabor the obvious, and he keeps the pace up. What is really impressive is how practical and accessible the book makes the technology of image processing.

One thing I have to point given my interest in the Raspberry Pi is that you can run all of the OpenCV and Python examples on your Raspberry Pi 2 and B+! How cool is that?

I highly recommend this book and its resources. I’m definitely a dilettante in this field but Practical Python and OpenCV + Case Studies has given me a lot more insight into the what and how it all works.If you’re interested in this field, you should also follow Rosebrock’s PyImageSearch blog.

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