The Open Source Computer Vision Library, or OpenCV if you prefer, houses over 2500 algorithms, extensive documentation and sample code for real-time computer vision.
OpenCV focuses mainly towards real-time image processing, as such, if it finds Intel's Integrated Performance Primitives on the system, it will use these commercial optimized routines to accelerate itself.
OpenCV library supports:
- Real-time capture.
- Video file import.
- Object detection.
- Basic image treatment: brightness, contrast, threshold.
- Blob detection
OpenCV can accomplish numerous different tasks including basic image processing, such as filtering, morphology, geometrical transformations, histograms, and color space transformations. It can also perform advanced image processing like inpainting, watershed & meanshift segmentation etc. OpenCV can also undertake more complex tasks such as contour processing and computational geometry, various feature detectors and descriptors (these can range from simple Harris detector to Hough transform, SURF, or MSER) object tracking, optical flow, object detection using cascades of boosted haar classifiers, camera calibration, and machine learning tools (data clustering and statistical classifiers).
The application is cross-platform and works on Windows, Mac OS X, Linux, Android and iOS.
# A lot of new functionality has been introduced during Google Summer of Code 2015:
* Several advanced calibration methods.
* Deep neural networks frameworks (without training).
* Improved text detection.
* Better stereo correspondence.
* New detection and tracking algorithms.
* Structure from motion and stereo 3D reconstruction.
* and more
# Many great contributions made by the community, such as:
* Support for HDF5 format.
* New/Improved optical flow algorithms.
* Multiple new image processing algorithms for filtering, segmentation and feature detection.
* Superpixel segmentation
* and much more.
# IPPICV is now based on IPP 9.0.1, which should make OpenCV even faster on modern Intel chips.
# opencv_contrib modules can now be included into the opencv2.framework for iOS.
# Newest operating systems are supported: Windows 10 and OSX 10.11 (Visual Studio 2015 and XCode 7.1.1).
#Interoperability between T-API and OpenCL, OpenGL, DirectX and Video Acceleration API on Linux, as well as Android 5 camera.
# HAL (Hardware Acceleration Layer) module functionality has been moved into corresponding basic modules; the HAL replacement mechanism has been implemented along with the examples.