Featured tutorials
Scanning QR Codes
Recognize QR Codes in images from scratch. We'll do all the bit math to figure out the location markers and then read data from the black/white array.
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SuDoKu Grabber in OpenCV
I decided to write a quick and fun project. The idea is simple - capture an image, identify the sudoku grid + digits and then solve the puzzle!
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Tracking colored objects in OpenCV
Given an object that is distinctly colored, you'll learn how to detect the object in the scene and track it as it moves across the frame - live!
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SIFT: Theory and Practice
Learn how the famous SIFT keypoint detector works in the background. This paper led a mini revolution in the world of computer vision!
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Generating Multivariate Gaussian Random Numbers
Given a covariance matrix and a mean vector, how do we generate random vectors from the corresponding Gaussian model?
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Expectation Maximization with Gaussian Mixture Models
Learn how to model multivariate data with a Gaussian Mixture Model. For training this model, we use a technique called Expectation Maximization.
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Finding dominant colors in an image
Here's a simple task - given an image find the dominant colors in the image. I'll walk you through a lesser known technique that does not use kmeans.
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Scanning QR Codes
Recognize QR Codes in images from scratch. We'll do all the bit math to figure out the location markers and then read data from the black/white array.
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The Canny Edge Detector
Read moreAn in-depth exploration of how the famous Canny edge detection system works. We'll implement our own after going through the theory.
Image Moments
Read moreImage moments help identify certain key characteristics in images - like the center, area of white pixels, etc. We'll look at how these are calculated mathematically.
The OpenCV 2 Computer Vision Application Programming Cookbook
Read moreThis is a something that their thing is the thing ahalsk the computer vision application programming cookbook and the thing over here is weird.
A super fast thresholding technique
Read moreLearn how to implement really fast thresholding - faster than OpenCV! This technique can be a useful addition to your arsenal of computer vision.
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