Human-Robot Collaboration (HRC) enabling mechanisms require real-time detection of potential collisions among human and robots. Taking under consideration the already existing standards and the literature, most of collision detection techniques require the integration of sensorial systems on the robot aiming to identify the contact events. This paper deals with a novel approach for the identification of human and robot collision based on vision systems. Moreover, Artificial Intelligent (AI) algorithms are required to classify the captured data near real-time and to provide a score about the collision status (contact or non-contact) between a human and the robot. Accordingly, the AI models should be trained using the appropriate image data enabling an accurate classification. The proposed system has been developed in a lab environment. A detailed presentation of the system implementation, its performance and the potential integration in a real industrial environment are discussed in this paper.