# Tag Archives | approximate contours

## Determining object color with OpenCV

This is the final post in our three part series on shape detection and analysis. Previously, we learned how to: Compute the center of a contour Perform shape detection & identification Today we are going to perform both shape detection and color labeling on objects in images. At this point, we understand that regions of an image […]

## OpenCV shape detection

This tutorial is the second post in our three part series on shape detection and analysis. Last week we learned how to compute the center of a contour using OpenCV. Today, we are going to leverage contour properties to actually label and identify shapes in an image, just like in the figure at the top of this post. […]

## OpenCV center of contour

Today, we are going to start a new 3-part series of tutorials on shape detection and analysis. Throughout this series, we’ll learn how to: Compute the center of a contour/shape region. Recognize various shapes, such as circles, squares, rectangles, triangles, and pentagons using only contour properties. Label the color of a shape. While today’s post is […]

## Target acquired: Finding targets in drone and quadcopter video streams using Python and OpenCV

I’m going to start this post by clueing you in on a piece of personal history that very few people know about me: as a kid in early high school, I used to spend nearly every single Saturday at the local RC (Remote Control) track about 25 miles from my house. You see, I used to […]

## Building a Pokedex in Python: Finding the Game Boy Screen (Step 4 of 6)

Quick question. How does a Pokedex work? Well, you simply point it a Pokemon, the Pokedex examines its physical characteristics, and the Pokemon is identified instantly. In this case, our smartphone camera is our “Pokedex”. We point our smartphone at our Game Boy, snap a photo of it, and our rival Pokemon is identified (if […]

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