Real-Time Image and Video Processing Applications Using Raspberry Pi - Yildirim, Merve; Karaduman, Ozgur; Kurum, Hasan (Institute of Electrical and Electronics Engineers Inc., 2022)
Image and video processing applications have significant importance in many areas which are the industrial and medical applications, especially the vehicular technology. To provide safe driving, Driving Assistance Systems (DAS) including detection and tracking of a road situation, objects and behavior of the driver should be considered by using the image processing algorithms. Since these applications need the processors having high speed and power, a Raspberry Pi platform meeting these specifications is used in this study. A Canny edge detector which is one of the important edge detection methods, face and eye detection, the road line tracking, motion detection, and object detection applications are handled. Conversely the studies in the literature which are separately examined these techniques, all of them are realized as a real-time based on the Rapberry Pi according to a video image taken by a camera. For this reason, OpenCv and TensorFlow libraries having widely computer vision algorithms and Python software language are used. It is observed that the results of all image and video processing applications are successful and satisfying. As a result, a safe and comfortable driving can be provided thanks to the proposed methods. © 2022 IEEE.
1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022 -- 9 December 2022 through 11 December 2022 -- Kharagpur -- 188946
Keywords: computer vision; edge detection; face detection; image and video processing; line tracking; motion detection; OpenCV; python; raspberry pi