Abstract- Due to road accidents in recent years; The development of surveillance systems with multifunctional techniques has received increasing attention. Using smart camera is a solution to solve traffic problems. Smart cameras are cameras that can perform tasks far beyond simply taking photos and recording videos. The intelligent traffic surveillance system (ITSS) is used to monitor roads to prevent accidents and at the same time identify the causes of accidents. This is done by implementing some image viewing protocols such as Gaussian and Canny. This paper will discuss the capabilities of video surveillance and camera tracking in diverse and varied road environments, including the detection of moving vehicles. The programming method used will be OpenCV functional programming which could be used with both Windows and Linux operating systems. This article will also look at the result of combining computer vision programming and network socket programming under GNU Linux. Ultimately, this article will attempt to engage in a discussion of the design issues, challenges, and future directions of this research. Keywords: ITSS intelligent traffic surveillance system, intelligent camera, image viewing, OpenCV, socket programming, GNU/Linux1. IntroductionObject recognition and detection are an important element in various fields of computer vision. The basic goal is to find an object in static images or video frames. In most cases, this task can be handled by extracting certain image features, such as edges, color areas, textures, outlines, shapes, etc. Subsequently, some techniques are applied to find configurations and combinations of those characteristics of the object you want to detect.......middle of paper......system. The systems were tested with different processor speeds, 2.6 GHz CPU processor, 2.2 GHz CPU processor, and 1.2 GHz CPU processor. The result is shown in Table 1; note that the average time count is expressed in ms.6. ConclusionA traffic surveillance system designed to monitor the safety level of the highway or highways and can be used in any background view and works even in 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, so vehicles are detected accurately. A vehicle video detection system was developed under GNU-Linux with C programming using the OpenCV function. The result attached to this paper goes beyond expectations as the purpose of the traffic surveillance system.