The visual detection and steering of medical autonomous vehicles

• Autorzy: Bernas M.
• Języki publikacji: EN

Abstrakty

EN

The paper presents initial research on method, which improves precise indoor localization and steering of autonomous mobile devices that can be used for medical applications like: patient’s state monitoring, medicine distribution or environmental data collection before medical intervention (in case of biohazard or fire). The localization of object is based on optical codes, which are modified to be easily identified from distance in low light. Multiple codes modification was tested to find optimal ones. The visual recognition system is using Hough transform and Canny edge detection to read values from code. The novelty of the proposed method is reading values directly from image, without scaling and rotation. Moreover, the steering algorithm for identified device is proposed. It takes distance and decision uncertainty under consideration. The proposed method was verified against state-of-the-art optical codes in real-world indoor environment. Finally, the further research directions are discussed.

Słowa kluczowe

EN

autonomous device; steering; optical code; Hough transform; first aid; medical parameters

PL

urządzenie autonomiczne; układ sterowania; kod optyczny; transformacja Hougha; pierwsza pomoc; parametry medyczne

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2015
• Tom: Vol. 24
• Strony: 133--140
• Opis fizyczny: Bibliogr. 18 poz., rys., tab., wykr.

Twórcy

autor

Bernas M.

• Institute of Computer Science, University of Silesia, Bedzinska 39, 41-200 Sosnowiec, Poland

Bibliografia

• [1] BASAK S., CHOWDHURY A. A vision interface framework for intuitive gesture recognition using color based blob detection. International Journal of Computer Applications (0975 8887), 2014, Vol. 90(15).
• [2] BERNAS M., PLACZEK B. Energy aware object localization in wireless sensor network based on wi-fi fingerprinting. CCIS, Computer Networks, Springer, 2015. pp. 33–42.
• [3] CHENGUANG Z., NA Y., RUKUN H. Study of two dimensional barcode identification technology based on hough transform. Journal of Changchun Normal University, 2007, Vol. 4. pp. 94–98.
• [4] CORONATO A. Towards an implementation of smart hospital: A localization system for mobile users and devices. Proc of. International Conference on Pervasive Computing and Communications, 2008, Vol. 6. pp. 715–719.
• [5] CZUSZYNSKI K. Interaction with medical data using qr-codes. Proc of International Conference on Human System Interactions (HSI), 2014, Vol. 7. pp. 182 – 187.
• [6] DONGHONG H., HUI T., XINMENG C. Radon transformation applied in two dimensional barcode image recognition. Journal of Wuhan University, 2005, Vol. 5. pp. 584–588.
• [7] ETIENNE J., ET A. Effect of automated drug distribution systems on medication error rates in a short-stay geriatric unit. Journal of Evaluation in Clinical Practice, 2014, Vol. 20(5).
• [8] KRAJNIK T., NITSCHE M., FAIGL J., VANEK P., SASKA M., PREUCIL L., DUCKETT T., MEJAIL M. A practical multirobot localization system. Journal of Intelligent & Robotic Systems, 2014, Vol. 76(3). pp. 539–562.
• [9] LI M., ZHAO W. Visiting power laws in cyber-physical networking systems. Mathematical Problems in Engineering, 2012, Vol. 302786. p. 13.
• [10] LIAO Z., HU S., SUN D., CHEN W. Enclosed laplacian operator of nonlinear anisotropic diffusion to preserve singularities and delete isolated points in image smoothing. Mathematical Problems in Engineering, 2011, Vol. 749456. p. 15.
• [11] MASZCZYK T., DUCH W. Comparison of shannon, renyi and tsallis entropy used in decision trees. Lecture Notes in Computer Science, 2008, Vol. 5097. pp. 643–651.
• [12] MINKYU L. Qrloc: User-involved calibration using quick response codes for wi-fi based indoor localization. Proc. of International Conference on Computing and Convergence Technology (ICCCT), 2012, Vol. 370. pp. 1460–1465.
• [13] PLACZEK B., BERNAS M. Optimizing data collection for object tracking in wireless sensor networks. Communications in Computer and Information Science (ISSN: 1865-0929), 2013, Vol. 370. pp. 485–494.
• [14] REDLARSKI G., PAKOWSKI A., AMBROZIAK D. Optical glyphs based localization and identification system. Pomiary, Automatyka, Robotyka, 2013. pp. 231–242.
• [15] SEENIVASAGAM V., VELUMANI R. A qr code based zero-watermarking scheme for authentication of medical images in teleradiology cloud. Computational and Mathematical Methods in Medicine(2013), 2014, Vol. 516465. p. 25.
• [16] SUN A., SUN Y., LIU C. The qr-code reorganization in illegible snapshots taken by mobile phones. International Conference on Computational Science and its Applications, 2007. pp. 532 – 538.
• [17] WENTING C., ZHI L. Two dimensional barcode localization algorithm based on convex. Journal of Zhejiang University, 2008, Vol. 46. pp. 669–672.
• [18] YAYAN U., AKAR B., INAN F., YAZICI A. Development of indoor navigation software for intelligent wheelchair. Proc of. IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA), 2014. pp. 23– 38.