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    OpenCV is a widespread computer vision and machine learning library applied in a great variety of contexts, including life sciences. The power of OpenCV relies on the huge amount (more than 2500) of both classic and state-of-the-art computer vision algorithms provided by this library. OpenCV supplies algorithms for: image processing, feature detection, object detection, machine-learning, and video analysis.

    Currently, the following alternatives allow to connect ImageJ/Fiji with OpenCV:

    • CVForge: an ImageJ plugin implementing a simple-to-use interface that gives access to all the methods of OpenCV.
    • IJ-OpenCV: a library to convert between ImageJ1 and OpenCV objects. It provides methods to convert images, ROI…

    From the perspective of ImageJ developers, they can use IJ-OpenCV to easily create plugins that use any functionality provided by the OpenCV library and explore different alternatives.
    From the perspective of OpenCV developers, this library provides a link to the ImageJ graphical user interface and all its features to handle regions of interest.

    • ImageJ-OpenCV is similar to IJ-OpenCV but provides converters between OpenCV and ImageJ2 types.
    • IJToolsUsingOpenCV: a suite of ImageJ plugins that connects ImageJ with some of the algorithms implemented in OpenCV.