Image Segmentation Using Color Spaces in OpenCV + Python | opencv color filter
Itmaybetheeraofdeeplearningandbigdata,wherecomplexalgorithmsanalyzeimagesbybeingshownmillionsofthem,butcolorspacesarestillsurprisinglyusefulforimageanalysis.Simplemethodscanstillbepowerful.Inthisarticle,youwilllearnhowtosimplysegmentanobjectfromanimagebasedoncolorinPythonusingOpenCV.ApopularcomputervisionlibrarywritteninC/C++withbindings[1]forPython,OpenCVprovideseasywaysofmanipulatingcolorspaces.Whileyoudon’tneedtobealreadyfamiliarwithOpenCVortheotherhelperpackagesusedinthisarticle,itisassu...
It may be the era of deep learning and big data, where complex algorithms analyze images by being shown millions of them, but color spaces are still surprisingly useful for image analysis. Simple methods can still be powerful.
In this article, you will learn how to simply segment an object from an image based on color in Python using OpenCV. A popular computer vision library written in C/C++ with bindings[1] for Python, OpenCV provides easy ways of manipulating color spaces.
While you don’t need to be already familiar with OpenCV or the other helper packages used in this article, it is assumed that you have at least a basic understanding of coding in Python[2].
What Are Color Spaces?In the most common color space, RGB (Red Green Blue), colors are represented in terms of their red, green, and blue components. In more technical terms, RGB describes a color as a tuple of three components. Each component can take a val...