Mohammad Hasan Olyaei Torqabeh - Faculty of Electrical Engineering, Sadjad University of Technology, Mashhad, Iran
Ali Olyaei Torqabeh - Department of Computer Engineering, Faculty of Engineering, Ferdowsi University ofMashhad, Mashhad, Iran

This paper discusses an algorithm for detecting bleeding in images taken from anendoscopic capsule. This algorithm consists of two parts. First, with deep learning,they instruct a deep network to distinguish between blood images and normal images.Then the images in the blood class are transmitted to the second part of the algorithm.In the second part, the images are converted to HSV and by comparing each pixel withthe threshold of blood, the location of the bleeding is marked and indicated by a greenrectangle. Simulation of this algorithm is implemented using the Python language andTensorflow. The results indicate that the deep network has been able to categorizewell between blood images and normal images, and the location of bleeding is alsoprominently indicated.

Deep Learning, Endoscopic Capsule, Bleeding Detection, Python, Tensorflow, HSV