Journal of Machinery Manufacturing and Automation 
Journal of Machinery Manufacturing and Automation(JMMA)
ISSN:2307-9096(Print)      2307-9088(Online)
Editor-in-Chief: Prof. Juntong Qi (China)
A Most-squares Solution for Separating Cars
Full Paper(PDF, 273KB)
This paper presents a method for finding the most-squares solution for separating cars, and intends to develop technologies to be able to separate cars from compact and standards based on images taken from the camera. Two major methods are used basically: 1. convex hulls algorithms to obtain car’s convex hull region and 2. classifying by separating cars into clusters regarding area and circumference of the regions obtained from car’s convex hull. Finally, a numerical example is presented.
Keywords:Separation; Clustering; Cars; Ferry; Linear Manifold for Separation; Convex Hull
Author: Makoto Katoh1, Masaki Ishitani2
1.Osaka Institute of Technology, Dept. of Mechanical Engineering, 5-16-1 Ohmiya, Asahi-ku, Osaka 535-8585, Japan
2.Graduate School of Osaka Institute of Technology, 5-16-1 Ohmiya, Asahi-ku, Osaka 535-8585, Japan
  1. T. Siithinaphong and K. Chamnongthai, “The recognition of car license plate for automatic parking system,” Fifth International Symposium on Signal Processing and Its Applications, ISSPA ’99, 1999, pp. 455-457.
  2. J. Katoh, T. Watanabe, and M. Yoneda, “HMM-based segmentation of background, object and shadow from traffic monitoring movies,” Transaction of Information Processing Society of Japan, vol. 42, no. 1, pp. 1-15, 2001.
  3. W. Hongjian, “Vehicle flow measuring based on temporal difference image,” IEEE Computer Society, 2009 Second International Conference on Intelligent Computation Technology and Automation, 2009, pp. 717-720.
  4. K. Taguchi, “Image processing type vehicle detection system,” Technical Report of Fukuyama University, 1997, pp. 13-18 (in Japanese).
  5. Takayama City in Japan, “Full Car and Empty Car Information of Parking Lot in Urban Takayama City,”, 2014.
  6. Yahoo, “Nationwide Japanese Cheap Ferry”,, 2014.
  7. B. Mirkin, “Clustering for data mining a data recovery approach,” Chapman & Hall/CRC, 2005, pp. 185-186.
  8. U. Maulik, S. Bandyopadhyay, and D. Plewczynski, “SVMeFC: SVM ensemble fuzzy clustering for satellite image segmentation,” IEEE Geoscience and Remote Sensing Letters, vol. 9, iss. 1, pp. 52-55, 2012.
  9. Y. Chu, J. Huang, K. Chung, et al., “Density conscious subspace clustering for high dimensional data,” IEEE Transaction on Knowledge and Data Engineering, vol. 22, iss. 1, pp. 16-30, 2010.
  10. M. Katoh, Basic Theory of Systems Control, Corona Publisher, Tokyo, 2014 (in Japanese).
  11. A. Albert, Regression and the Moore-Penrose Pseudo Inverse, Academic Press, 1974.
  12. T. Kohonen, Self-Organizing Maps, 2nd ed., Springer, 1995.
  13. D. G. Luenberger, Optimization by Vector Space Methods, John Wiley & Sons, Inc., 1969.
  14. Open CV Dev Team, “Open CV Tutorials,”, 2014.