Tutorials – Setup OpenCV for Android, iOS, Linux, and Windows


OpenCV (open source computer vision) was developed for real-time computer vision applications and is used widely in robotics for vision applications like facial recognition, gesture recognition, human–computer interaction, in mobile robotics for object identification, segmentation and recognition, motion tracking, augmented reality, and the list can continue.

With a large support for operating systems like Windows, Linux, Mac OS, iOS or Android, in the following are available a series of tutorials that covers everything about how to setup the OpenCV software on all these operating systems.

Setup OpenCV

OpenCV in Robotics

With an opened platform, Open Source Computer Vision is one of the most used real-time vision software in robotics for educational, hobbyists or research purposes. It is written in C++ and has its interface compatible with C++, Python, Java, and Matlab/Octave.

The latest version 2.4.8 of OpenCV was released at the end of 2013 and is available here for the above operating systems:

The following tutorials explored common installations and configuration requirements on several platforms in order to start developing vision applications for robots.

Setup OpenCV on Android and Examples

Even is a robot that runs Android OS, or a robot controlled with a mobile devices such as smartphones and tablet computers that runs Android OS, the operating system based on the Linux kernel is widely adopted in the robotics community to acquire, process, analyze and understand images.

In the following, I explore several tutorials from where you can learn how to install the OpenCV on Android OS, how to use the vision software with development environments, as well as many more resources to start develop applications.

  • Introduction to OpenCV – this tutorial is part of the official documentation for OpenCV 2.4.8 and is the starting point in working with OpenCV and Android OS. Even was written for Windows 7 users, it should work with Linux and Apple Mac OS as well. Following all the well documented steps of this tutorial, finally you have a development environment based on Eclipse ready for your first own application;
  • Using Android binary package with Eclipse – a guide that follows step by step the setup of Android development environment on all operating systems supported by Android SDK including Windows 7, Linux Ubuntu, or Mac OS;
  • Introduction into Android Development – a guide that helps you to learn the basics of Android and OpenCV development on Windows 7, Linux Ubuntu, Mac OS X, or any other operating system supported by Android SDK;
  • OpenCV on Android – based on the OpenCV 2.4.3 version, this is another tutorial from where you can learn how to setup the OpenCV on Eclipse and start working on Android Virtual Device Manager;
  • Building OpenCV4Android from trunk – comprehensive tutorial how to setup the Android NDK, CMake, and OpenCV on different operating systems including Windows, Mac OS, and Linux;


  • Get started with OpenCV on Android – from this tutorial you can learn how to get started with OpenCV version 2.4.3 on Android, how to capture and process images from the Android camera with OpenCV, as well as display the results of the processed image;
  • OpenCV Tutorial 1: Camera Preview – if you have finally done successfully the installation of OpenCV for Android OS, this could be a good exercise to understand how Android OS and OpenCV are interfaced to have a camera preview of your mobile device;
  • Android eye detection updated for OpenCV 2.4.6 – finally you can build the first real-time application that highlight the true power of the OpenCV software;

Setup OpenCV on iOS and Examples

Since was renamed as iOS on 2010, the operating system became a main point in the Apple marketing literature as a common operating system for the iPhone, iPad, and iPod Touch. The iOS has definitely impressed features for robotic applications, while a list with tutorials and examples will demonstrate the sense of using iOS with OpenCV.

  • Installation in iOS – short guide to follow for OpenCV setup to run with iOS using CMake and Command Line;
  • Installing OpenCV for iOS – from this tutorial you can learn step by step how to setup the OpenCV to work with iOS operating system and start building applications in minutes;
  • Building OpenCV for iPhone in one click – sometimes you can use shortcuts to reach the ultimate goal, and in this tutorial you can find the right script to build the OpenCV library for the iPhone, iPad, and any other device that runs the iOS operating system;


Setup OpenCV on Windows Phone and Example

Things went slowly between the OpenCV and Windows Phone and there are real plans to support the Windows Phone 8 in the following versions. Regarding Windows Phone 7, the situation is slightly better with more information and fewer applications.

This section will be updated with tutorials and applications after official support of OpenCV for WP 7 and WP 8.

  • Face Detection For Windows Phone 7 – this is a guide that shows you how to use a library built for Windows Phone OS to perform a face detection application with OpenCV and Windows Phone 7;

Setup OpenCV on Linux and Examples

One of the most common operating system in robotics is Linux and this is a good reason to explore a long list with tutorials that explain you how to setup the OpenCV framework on different Linux versions, and learn how to build vision applications from several examples.

  • Installation in Linux – the official OpenCV setup tutorial on Linux Ubuntu 10.04 or later;
  • OpenCV – this is an installation guide of OpenCV on Linux Ubuntu;
  • Installing OpenCV on Debian Linux – a complete tutorial from where you can learn how to setup OpenCV 2.4.2 or 2.4.3 on Linux Debian;
  • Installation on Linux – installation steps and details how OpenCV can run together with the Code Blocks IDE to build visual applications;


Setup OpenCV on Windows and Examples

The OpenCV community includes a complete support for all Windows PC versions and for development environments such as Visual Studio or NetBeans IDE. Given the wide range of operating system version, I try to cover with tutorials and examples the most used Windows versions including here the Windows 7 and Windows 8 operating systems.

Setup OpenCV on Mac OS and Examples

This article was last modified on 03 February 2014.

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