Real-time Vehicle Surveillance System Based on Image Processing and Short Message Service
This paper proposes a real-time vehicle surveillance system based on image processing approach tailored with short message service. A background subtraction, color balancing, chain code based shape detection, and blob filtering are used to detect suspicious moving human around the parked vehicle. Once detected, the developed system will generate a warning notification to the owner by sending a short message to his mobile phone. The current frame of video image will also be stored and be sent to the owner e-mail for further checking and investigation. Last stored image will be displayed in a centralized monitoring website, where the status of the vehicle also can be monitored at the same time. When necessary, the stored images can be used during investigation process to assist the authority to take further legal actions.
 M. Carvalho, “No. 6 on the world’s top car theft list,” The Star, Aug. 25, 2016. https://www.thestar.com.my/news/nation/2016/08/25/no-6-on-the-worlds-top-car-theft-list-about-60-vehicles-stolen-everyday-from-all-over-malaysia-says/. (accessed Feb. 21, 2021).
 J. P. Jeong and T. T. Oh, “Survey on protocols and applications for vehicular sensor networks,” International Journal of Distributed Sensor Networks, vol. 12, no. 8, Aug. 2016.
 Y. Hori, Y. Sasaki, I. Miyamatsu, and S. Yakura, “Development of Intrusion Detection Sensor for Vehicle Anti-theft Systems,” Fujitsu Ten Tech. J., no. 23, pp. 26–31, 2000.
 K. P. Tanna, P. Kumar, and S. Narayanan, “Instant Theft Alert and Tracking System in Car,” International Journal of Computer Applications, vol. 1, no. 21, pp. 975–8887, 2010.
 H. S. Kaashif, H. J. J. Antony, S. R. Raj, and D. Nithya, “Automobile Intrusion Avoidance Using Face Detection and Finger Print,” International Journal of Computer Applications, no. 2, pp. 2278–8948, 2013.
 Z. Tufail, K. Khurshid, A. Salman, I. F. Nizami, K. Khurshid, and B. Jeon, “Improved Dark Channel Prior for Image Defogging Using RGB and YCbCr Color Space,” IEEE Access, vol. 6, pp. 32576–32587, Jun. 2018.
 R. C. Gonzalez and R. E. Woods, Digital Image Processing, 4th ed. Pearson, 2018.
 I. Zeger, S. Grgic, J. Vukovic, and G. Sisul, “Grayscale Image Colorization Methods: Overview and Evaluation,” IEEE Access, vol. 9, pp. 113326–113346, 2021.
 K. J. Chen and S. Y. Fang, “Printability Enhancement with Color Balancing for Multiple Patterning Lithography,” IEEE Transactions on Emerging Topics in Computing, vol. 7, no. 2, pp. 244–252, 2019.
 F. Gasparini and R. Schettini, “Color balancing of digital photos using simple image statistics,” Pattern Recognition, vol. 37, no. 6, pp. 1201–1217, 2004.
 P. M. Jodoin, J. Konrad, and V. Saligrama, “Modeling background activity for behavior subtraction,” presented at the 2008 2nd ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC 2008, 2008.
 J. Su, “Illuminant Estimation: Gray World,” 2015. https://web.stanford.edu/~sujason/ColorBalancing/grayworld.html (accessed Feb. 21, 2021).
 G. Boato, D. T. Dang-Nguyen, and F. G. B. D. Natale, “Morphological Filter Detector for Image Forensics Applications,” IEEE Access, vol. 8, pp. 13549–13560, 2020.
 C. Solomon and T. Breckon, Fundamentals of Digital Image Processing: A Practical Approach with Examples in MATLAB. Wiley-Blackwell, 2012.
 H. Haron, S. M. Shamsuddin, and D. Mohamed, “Chain Code Algorithm in Deriving T–Junction and Region of a Freehand Sketch,” Jurnal Teknologi, Jan. 2012.
 J. Sun and X. Wu, “Chain code distribution-based image retrieval,” in 2006 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2006, 2006, pp. 139–142.
 Y. Xie, P. K. Hopke, G. Casuccio, and B. Henderson, “Use of chain code histogram method to quantify airborne particle shapes,” Aerosol Science and Technology, vol. 21, no. 3, pp. 210–218, Jan. 1994.
 C. Coronel and S. Morris, Database Systems Design, Implementation, & Management, 13th ed. Cengage, 2019.
 H. J. Bhatti and B. B. Rad, “Databases in Cloud Computing: A Literature Review,” International Journal of Information Technology and Computer Science, vol. 9, no. 4, pp. 9–17, Apr. 2017.
 M. Čihař, “The Gammu Manual,” 2015. https://docs.gammu.org/ (accessed Feb. 22, 2021).
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