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 exist to connect ImageJ and/or ImageJ2 with OpenCV:
-
PyImageJ: a Python wrapper for ImageJ2 enabling access to all of ImageJ2 and the original ImageJ from Python. Together with opencv-python, the two programs can be used together with NumPy arrays as a common data structure.
-
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 original ImageJ data structures and OpenCV objects.
-
ImageJ-OpenCV is similar to IJ-OpenCV but provides converters between OpenCV and ImageJ2 types.
-
IJToolsUsingOpenCV: a suite of plugins for the original ImageJ that connects ImageJ with some of the algorithms implemented in OpenCV.
