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Pattern Recognition Through Digital Image Processing for Unmanned Aerial Vehicles
IEEE Access. 2019. Article 1.
Bhimani K. R., Gabino R. V., Prakosa J.
Editor of translation: A. B. Alvarez
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.
Language:
English
Keywords: распознавание образовdigital image processingбеспроводная связьvideo streamingWireless Communicationsdronesдроныцифровая обработка изображений pattern recognitionBoundary color detectionHaar Cascade method for customized object detectionAerial robotsОбнаружение граничного цветаКаскадный метод Хаара для индивидуальных обнаружение объектаВидео трансляцияВоздушные роботы
IEEE, 2026.
Proceedings of the X Scientific School "Dynamics of Complex Networks and their Applications"
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