Integration of Morphological Operators in Neural Networks



Image processing is a very broad field of study that encompasses a multitude of operations, each of them with different purposes and circumstances of use, complexities and results. Nowadays, the bests results for automatic image study (image segmentation, image classificationobject detection, etc.) are obtained using deep learningand more specifically convolutional neural networks. We explore and conduct experiments on a specific part of image processing, mathematical morphology, investigating on the best way of circumventing operations' complexities regarding their integration in a supervised learning pipeline.