OpenCV

OpenCV Logo with text svg version

OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was designed to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code.

The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, stitch images together to produce a high resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery and establish markers to overlay it with augmented reality, etc.

OpenCV supports a wide variety of programming languages such as C++, Python, Java, and operates on various platforms including Windows, Linux, OS X, and Android. The library is cross-platform and free for use under the open-source BSD license.

History

OpenCV was started at Intel in 1999 by Gary Bradski and the first release came out in 2000. Vadim Pisarevsky joined Gary Bradski to manage Intel’s Russian software OpenCV team. In the early days of OpenCV, the goals of the project were described as:

• Advance vision research by providing not only open but also optimized code for basic vision infrastructure. No more reinventing the wheel.
• Disseminate vision knowledge by providing a common infrastructure that developers could build on, so that code would be more readily readable and transferable.
• Advance vision-based commercial applications by making portable, performance-optimized code available for free – with a license that did not require to be open or free themselves.

Features

OpenCV specializes in real-time image processing and includes patented algorithms that are used for commercial purposes. Its features include:

• Facial recognition system
• Gesture recognition
• Human-computer interaction (HCI)
• Mobile robotics
• Motion understanding
• Object identification
• Segmentation and recognition
• Stereopsis stereo vision: depth perception from two cameras
• Structure from motion (SFM)
• Video tracking
• Augmented reality

Applications

The use of OpenCV extends beyond the above-mentioned features. It is used in security systems, driver assistance systems, medical imaging systems, street view image stitching, interactive art installations, and many more areas. It has become a go-to library for companies and developers looking to employ computer vision in their products.

Development and Community

OpenCV's development is now supported by a community of contributors and a non-profit organization, the Open Source Robotics Foundation (OSRF), which manages the distribution. The library continues to grow and evolve, with new algorithms and features being added regularly. The community around OpenCV is vast, with an extensive network of users contributing to forums, documentation, and tutorials, making it an accessible technology for newcomers to computer vision.

See Also

• Machine Learning
• Computer Vision
• Artificial Intelligence
• Image Processing