Image Segmentation for One Way Video Traffic Using Background Substraction Method

Current technological developments are experiencing a rapid increase, one of the areas that have increased is pattern recognition. Data or information of movement process of an object can be presented in video form. Video is a composite image / dead images that are read sequentially at a time with a certain speed. Image is something that describes the object. While digital image is an image that has been stored in the form of a file so it can be processed using a computer. Digital image processing techniques can be applied in the process of image segmentation. OpenCV is a library that contains programming functions for real-time computer vision technology. OpenCV already uses the C # language interface and all its development is in C # language format. Examples of applications from OpenCV are human and computer interactions; identification, object segmentation and recognition, face recognition, motion recognition and movement tracking. By utilizing traffic video containing one way traffic flow, then made a vehicle detection program with background substraction method. This research can detect moving objects (vehicles). In the process of testing a video with .avi extension. Then from the video will be segmented thresholding image to find the moving object. Then, a background and foreground separation sequence is performed to separate moving objects with non-moving objects of a certain value.