Summary - Due to road accidents occurring in recent years; the development of monitoring systems with multifunctional techniques is receiving increasing attention. Using smart camera is a solution to solve traffic problems. Smart cameras are cameras that can perform tasks far beyond just taking photos and recording videos. Intelligent Traffic Monitoring System (ITSS) is used to monitor roads to prevent accidents while finding the causes of accidents. This is done by implementing certain image vision protocols like Gaussian and Canny. This article will discuss the capabilities of tracking video surveillance cameras in different and varied road environments, including the detection of moving vehicles. The programming method used will be OpenCV functional programming which can be used under Windows and Linux operating systems. This article will also look at the result of combining computer vision programming and network socket programming in GNU Linux. At the end, this article will attempt to provide a discussion on the design issues, challenges, and future directions of this research. Keywords: ITSS intelligent traffic monitoring system, intelligent camera, image vision, OpenCV, Socket programming, GNU/Linux1. IntroductionObject recognition and detection is an important element in various fields of computer vision. The basic objective is to find an object in static images or video images. Most of the time, this task can be done by extracting some features from the image, such as edges, color regions, textures, contours, shapes, etc. Then, certain techniques are applied in order to find configurations and combinations of the characteristics of the object that one wishes to detect....... middle of paper ...... system. The systems were checked with different processor speeds, 2.6 GHz CPU processor, 2.2 GHz CPU processor and 1.2 GHz CPU processor. The result is illustrated by table 1; note that the time average counts in ms.6. ConclusionA traffic monitoring system designed to monitor the safety level of the highway or highways and can be used in any background view, it also works on rainy and sunny days, even at night; The vehicle detection algorithm was designed using both Canny and Gaussian protocols. The background is updated in real time and is useful for performing background subtraction and then the vehicles were detected accurately. A vehicle video detection system was developed under GNU-Linux with C programming using the OpenCV function. The result as presented in this paper exceeds expectations regarding its purpose for the traffic monitoring system..