IJ-OpenCV: Combining ImageJ and OpenCV for processing images in biomedicine

Background and Objective. The effective processing of biomedical images usually requires the interoperability of diverse software tools that have different aims but are complementary. The goal of this work is to develop a bridge to connect two of those tools: ImageJ, a program for image analysis in life sciences, and OpenCV, a computer vision and machine learning library. Methods. Based on a thorough analysis of ImageJ and OpenCV, we detected the features of these systems that could be enhanced, and developed a library to combine both tools, taking advantage of the strengths of each system. The library was implemented on top of the SciJava converter framework. We also provide a methodology to use this library. Results. We have developed the publicly available library IJ-OpenCV that can be employed to create applications combining features from both ImageJ and OpenCV. 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. Conclusions. The IJ-OpenCV library bridges the gap between ImageJ and OpenCV, allowing the connection and the cooperation of these two systems.