Abstract
With a vision of proposing a fully automated parking management solution for smart parking, in which all the operations in the process of parking will be automated. And as a first step we will focus on vehicle localization inside parking based on image processing theory. Video based localization algorithms present an important interest in the field of intelligent video surveillance, the integration of such functionality in the surveillance system will revolt their classic roles. Navigation tool and other amazing systems can easily build based on such feature. This paper describes an implementation of a FPGA based real-time visual system for vehicle localization. Vehicle in the video frames are extracted after the application of the background subtraction method on the input image using a background reference image. The dynamic threshold used is computed by the Otsu method. Finally, the object mask resulting from the segmentation process is used to compute the relative distance to the camera based on the relation between the ratio of the size of a vehicle on the camera sensor and its size in real life which is a function of the camera focal length and distance between the vehicle and the camera. The experimental results show that the proposed system is sufficiently satisfying the real time constraint (under the 100 MHz frequency a 32 frames per second is achieved for the 1440 * 1080 resolution, and under 50 MHz frequency a 41 frames per second is achieved for the 640 * 480 resolution) with an accuracy error around the centimeter level.
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Ureña, J., Gualda, D., Hernández, Á., García, E., Villadangos, J.M., Pérez, M.C., García, J.C., García, J.J., Jiménez, A.: Ultrasonic local positioning system for mobile robot navigation: from low to high level processing. In: 2015 IEEE International Conference on Industrial Technology (ICIT), pp. 3440–3445, 17–19 March 2015. https://doi.org/10.1109/ICIT.2015.7125610
Ijaz, F., Yang, H.K., Ahmad, A.W., Lee, C.: Indoor positioning: a review of indoor ultrasonic positioning systems. In: 2013 15th International Conference on Advanced Communications Technology (ICACT) (2013)
Huang, C.-H., Lee, L.-H., Ho, C.C.: Real-time RFID indoor positioning system based on Kalman-Filter drift removal and Heron-Bilateration location estimation. IEEE Trans. Instrum. Meas. 64(3), 728–739 (2015). https://doi.org/10.1109/TIM.2014.2347691
Wang, C.-S., Chen, C.-L.: RFID-based and Kinect-based indoor positioning system. In: 2014 4th International Conference on Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems (VITAE) (2014). https://doi.org/10.1109/vitae.2014.6934458
Xu, H., Ding, Y., Wang, R., Shen, W., Li, P.: A novel Radio Frequency Identification three-dimensional indoor positioning system based on trilateral positioning algorithm. J. Algorithms Comput. Technol. 10(3), 158–168 (2016)
Wang, Y., Yang, X., Zhao, Y., Liu, Y., Cuthbert, L.: Bluetooth positioning using RSSI and triangulation methods. In: 2013 IEEE 10th Consumer Communications and Networking Conference (CCNC) (2013). https://doi.org/10.1109/CCNC.2013.6488558
Yang, C., Shao, H.: WiFi-based indoor positioning. IEEE Commun. Mag. 53(3), 150–157 (2015). https://doi.org/10.1109/mcom.2015.7060497
Hofmann-Wellenhof, B., Lichtenegger, H., Collins, J.: Global Positioning System Theory and Practice, vol. 1. Springer, Vienna (2001)
La Delfa, G.C., Catania, V., Monteleone, S., De Paz, J.F., Bajo, J.: Computer vision based indoor navigation: a visual markers evaluation. In: Mohamed, A., Novais, P., Pereira, A., Villarrubia González, G., Fernández-Caballero, A. (eds.) Ambient Intelligence - Software and Applications. AISC, vol. 376, pp. 165–173. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19695-4_17
Wolcott, R.W., Eustice, R.M.: Visual localization within LIDAR maps for automated urban driving. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (2014). https://doi.org/10.1109/iros.2014.6942558
Vala, M.H.J., Baxi, A.: A review on Otsu image segmentation algorithm. Int. J. Adv. Res. Comput. Eng. Technol. (IJARCET) 2(2), 387 (2013)
Background models challenge. http://bmc.iut-auvergne.com/
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005). https://doi.org/10.1109/cvpr.2005.177
Malisiewicz, T., Gupta, A., Efros, A.A.: Ensemble of exemplar-SVMs for object detection and beyond. In: 2011 International Conference on Computer Vision (2011)
Einsiedler, J., Sawade, O., Schäufele, B., Witzke, M., Radusch, I.: Indoor micro navigation utilizing local infrastructure-based positioning. In: 2012 IEEE Intelligent Vehicles Symposium (2012). https://doi.org/10.1109/ivs.2012.6232262
Ibisch, A., Houben, S., Schlipsing, M., Kesten, R., Reimche, P., Schuller, F., Altinger, H.: Towards highly automated driving in a parking garage: general object localization and tracking using an environment-embedded camera system. In: 2014 IEEE Intelligent Vehicles Symposium (IV), 8–11 June 2014, Dearborn, Michigan, USA (2014). https://doi.org/10.1109/ivs.2014.6856567
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Lahdili, H., Alaoui Ismaili, Z.E.A. (2018). Visual Vehicle Localization System for Smart Parking Application. In: Ben Ahmed, M., Boudhir, A. (eds) Innovations in Smart Cities and Applications. SCAMS 2017. Lecture Notes in Networks and Systems, vol 37. Springer, Cham. https://doi.org/10.1007/978-3-319-74500-8_34
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DOI: https://doi.org/10.1007/978-3-319-74500-8_34
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