In this thesis, 3D positioning of objects in a closed environment was implemented in real time using a few inexpensive cameras. Although the GPS (Global Positioning System) is widely used to determine the position of objects However, GPS is more accessible to open spaces, and cannot be used for positioning in all environments. A lot of research has been done to determine the position in indoor environments, but still due to limitations in machine vision and device processing capabilities, determining the position of an object in real time is a challenging issue. Challenges such as high-speed processing required for real-time, full coverage of the environment, high volumes of data, and synchronization of images cause incorrect response. In this thesis, we have tried to find the 3D position of an object in real time using several fixed cameras. The proposed algorithm for 3D positioning is divided into three stages detection, tracking and positioning which all stages being implemented in parallel. The system at the detection stage finds the target using the image matching algorithm without knowing previous position, and then it is transmitted to the tracking stage. In the tracking step, the target is tracked using the KCF algorithm, and if the target goes out of the image, the system returns to the detection stage. Then the target's 2D position is sent to the distributed Kalman filter. In the distributed Kalman filter, 2D positions are combined and 3D position is obtained from a fixed coordinate system based on the centimeter. In the proposed algorithm, the parallel programming languages MPI and OPENMP have been used to increase the speed and accuracy of the program. In this thesis, the time response of seven morphological operations such as dilation, erosion, opening, closing, morphological gradient, top hat and black hat, has been improved with parallel processing methods. The results have shown that the system succeeded in calculating a maximum of 180 3D positions in a second with a precision of at least two centimeters from each coordinate axis. Keywords: 1- Real-time positioning 2- Object detection and tracking 3- Distributed Kalman Filter 4- Morphological operation