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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Olivia Rumiris Sitanggang
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Sistem Deteksi dan Pengenalan Jenis Rambu Lalu Lintas Menggunakan Metode Shape Detection Pada Raspberry Pi Olivia Rumiris Sitanggang; Hurriyatul Fitriyah; Fitri Utaminingrum
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The traffic sign recognition is the digital image processing technology that used to recognize the sign in real-time. This technology applied in the Driver Assistance System. The road sign recognition consist of 2 main phase, they are road detection and recognition. Detection is the phase to find the possibility of picture area where the sign is located. The output from the detection process is the result picture segmentation that contain region of interest that can recognize the potential area of where the road sign being located. Those potential area will be affected the input of recognition process. So built a system of detection and recognition of the type of signs. This system is implemented on raspberry pi and real-time when processing the image of road sign from webcacm. The detection of algorithm consist into three main part, they are color segmentation, shape detection, and road classification. The method that being applied in this research is shape recognition method. This method is supported by the amount of point from the object as a representation of the amount of side from every shape and the comparison of object area with the bounding rectangle. And the output of this system is a kind of the sign notification for drivers. It is expected with this method the detection process to find the accurate regional sign recognition. The level of success in detecting kind of command signs, prohibition, and warning sign are 80.7%, the result of color examination from the three signs reach the number of 85.45%, and the result of presentation in recognizing the shape of sign is 80.7%. the duration of detecting of traffic signals is 0.5 seconds (for each frame) or 2 frames per second with detection distance 2-5 meters.
Co-Authors Fitriyah, Hurriyatul Utaminingrum, Fitri