Metoda wektoryzacji obrazu sceny dla autonomicznego robota

• Autorzy: Śmigielski P.

Warianty tytułu

EN

Scene vectorization method for an autonomous robot

• Języki publikacji: PL

Abstrakty

EN

The aim of the studies was to design, implement and test the algorithm for vectorization of the scene, which is analyzed by an autonomous robot. The vectorization is the process of extraction of the contours of the objects located in the image taken by a camera. The result is stored in a computer's (robot's) memory as a sequence of points in euclidean space marking the examined objects' corners. During the tests, various images were used. Each one was previously pre-processed in a different way in order to reveal and highlight the contours of the objects. The vectorization process is divided into three steps which are described in detail in this article.

Słowa kluczowe

PL

wektoryzacja; analiza sceny; model sceny; robot autonomiczny

EN

vectorization; scene analysis; scene model; autonomous robot

• Wydawca: ADVSEO sp. z o. o.
• Czasopismo: Technical Issues
• Rocznik: 2015
• Tom: nr 4
• Strony: 32--38
• Opis fizyczny: Bibliogr. 7 poz., rys.

Twórcy

autor

Śmigielski P.

• Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie Wydział Elektrotechniki, Automatyki, Informatyki i Inżynierii Biomedycznej Katedra Informatyki Stosowanej Al. Mickiewicza 30 30-059 Kraków

Bibliografia

• 1. Bonin-Font, F., Ortiz, A., Oliver, G., Visual navigation for mobile survey, Journal of Intelligent and Robotic Systems, 2008, 53, pp. 263–296.
• 2. Muratet, L., Doncieux, S., Briere, Y., Meyer, J.A., A contribution to vision-based autonomous helicopter flight in urban environments, Robotics and Autonomous Systems, 2005, 50, pp. 195–229.
• 3. Hrabar, S., Sukhatme, G. S., Corke, P., Usher, K., Roberts, J., Combined optic-flow and stereo-based navigation of urban canyons for a UAV. In Proceedings of the international conference on intelligent robots and systems IROS’2005, pp. 3309–3316.
• 4. Liu, J., Liu, D., Cheng, J., Tang, Y., Conditional simultaneous localization and mapping: A robust visual SLAM system, Neurocomputing, 2014, 145, pp. 269–284.
• 5. Strasdat, H., Montiel, J.M.M., Davison, A.J., Visual SLAM: Why filter? Image and Vision Computing, 2012, 30, pp. 65–77.
• 6. Bielecki, A., Buratowski, T., Śmigielski, P., 2013. Recognition of two-dimensional representation of urban environment for autonomous flying agents, Expert Systems with Applications, 2013, 40, pp. 3623–3633.
• 7. Canny, J. 1986. A Computational Approach To Edge Detection, Pattern Analysis and Machine Intelligence, 1986, 8, pp. 679–698.