Pattern Recognition Through Digital Image Processing for Unmanned Aerial Vehicles
Gabino Rey Vidangos Ponce, Kishankumar Bhimani, Jalu Ahmad Prakosa, Ana Beatriz Alvarez · 2019
This paper describes the implementation of two digital image processing methods for pattern recognition, by color boundary method and the Haar Cascade Classifier to detect objects in a video stream, both methods implemented on Python 3 and OpenCV. Patterns detection of images obtained from drones has advantages over traditional video recording drones. The drone has a streaming video system, based on the Raspberry Pi 3 minicomputer, which is sent by wireless communication to the base station where a pattern recognition algorithm performs operations on the video source coming from the drone. This proposed system has excellent performance based on an integrated streaming video system with 5.8GHz Wi-Fi connection acceptable to the base station. Both methods proved to be valid for certain types of patterns and objects under different light conditions.