Image Segmentation for One Way Video Traffic Using Background Substraction Method

Maslim, Martinus and Dwiandiyanta, B. Yudi and Epardi, Jourgi (2017) Image Segmentation for One Way Video Traffic Using Background Substraction Method. In: International Conference on Computer Science and Artificial Intelligence CSAI 2017, 5-7 Desember 2017, Jakarta.

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Abstract

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 realtime 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 nonmoving objects of a certain value.

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