Mehrdad Javadi; Mehdi Ebrahimi

Fast Width Detection in Corridor Using Hough Transform

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Author(s)

Mehrdad Javadi ^1,* Mehdi Ebrahimi ¹

1. Department of Mechatronics, Islamic Azad University, South Tehran Branch

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2012.12.07

Received: 10 Aug. 2012 / Revised: 12 Sep. 2012 / Accepted: 17 Oct. 2012 / Published: 8 Nov. 2012

Index Terms

Vision based, Width detection, Navigation, Hough transform, Robot

Abstract

For many robotics and smart car applications it is vitally important to calculate the width. The present paper proposes a new approach for finding the width of a corridor within a constructed image frame that would keep a robot on a safe track away from walls. The main advantage of this approach is less computation time and hence faster response for path recognition. In this new approach, the Hugh Transform technique is also used as the basis of the provided algorithm. Within the determination of corridor width, in order to avoid the accident in the future researches, some approaches such as identify open space, modeling and reconstruction of three-dimensional space, can also be used.

Cite This Paper

Mehrdad Javadi,Mehdi Ebrahimi,"Fast Width Detection in Corridor Using Hough Transform", IJIGSP, vol.4, no.12, pp.50-56, 2012. DOI: 10.5815/ijigsp.2012.12.07

Reference

[1]J. Michels, A. Saxena and A. Y. Ng. “High Speed Obstacle Avoidance using Monocular Vision and Reinforcement Learning”, Proc.22nd Int. Conf. Machine Learning, pp. 593–600,2005.

[2]P.V.C. Hough , “Method and Means for Recognizing Complex Patterns”, U.S. Patent 3,069,654, Dec. 18, 1962.

[3]R.O. Duda, P. E. Hart, ”Use of the Hough Transformation to Detect Lines and Curves in Pictures”, Commun. ACM, Vol.15, No. 1,pp. 11-15.1972

[4]M.A. Fischler and R.C. Bolles, (1981) “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography”, Commun. ACM, Vol. 24, No. 6, pp. 381-395,1981.

[5]H. Kalviainen, P. Hirvonen, “An Extension to the Randomized Hough Transform Exploiting Connectivity”, Pattern Recognition Letters, Vol. 18, No.1, pp. 77-85, 1997.

[6]V. Kyrki and H. Kalviainen ,“Combination of Local and Global Line Extraction”, Real-Time Imaging, Vol. 6, pp. 79-91, 2000.

[7]T.C. Chen, K.L. Chung, “A New Randomized Algorithm for Detecting Lines”, RealTime Img., Vol. 7, No. 6, pp. 473-481, 2001.

[8]J.B. Bums, A.R. Hanson, E.M. Riseman, “Extracting straight lines”, IEEE Trans. Pattern AnaL Machine Intell., vol. 8, no. 4, pp. 425-455, 1986.

[9]P. Kahn, , L. Kitchen, E.M. Riseman, “A Fast Line Finder for Vision-Guided Robot Navigation”, IEEE Trans. Pattern AnaL Machine Intell., Vol. 12, No. 11, pp. 1098-1102, 1990.

[10]R.F. Vassallo, H.J. Schneebeli, J. Santos-Victor, “A purposive strategy for visual-based navigation of a mobile robot”, Proc. Circuits and Systems , pp. 334-337, Aug. 1998.

[11]W.Shi, J.Samarabandu, “Corridor Line Detection for Vision Based Indoor Robot Navigation”,Canadian Conference on Electrical and Computer Engineering , PP.1988-1991, 2006.

[12]A.R. Brouwer, “Adaptive edge detection and line extraction for the Vision Survey System”, M.Sc. Thesis Eindhoven University of Technology , 1994.

[13]A. V. Nefian, G. R. Bradski, “Detection Of Drivable Corridors For Off-Road Autonomous Navigation”, IEEE Int. Conf. on Image Processing ICIP 2006, 3025 - 3028 2006.

[14]A.M. Zou, Z.G. Hou, M. Tan, D. Liu,“Vision-Guided Mobile Robot Navigation”, Proc. IEEE Int. Conf. Networking, Sensing and Control , pp. 209-213, 2006.

[15]P. Kahn, L. Kitchen, E.M. Riseman, “A fast line finder for vision-guided robot navigation”, IEEE Trans. Pattern Anal. And Machine Intell., vol.12, No.11, pp. 1098-1102, Nov. 1990.

[16]J. B. Burns, A. R. Hanson, E. M. Riseman, “Extracting straight lines”, IEEE Trans. Pattern Anal. Machine Intell., Vol. 8, No. 4,pp. 425-455, 1986.

[17]J. Samarabandu, W. Shi, “Corridor Line Detection For Vision Based Indoor Robot Navigation”, Canadian Conference on Electrical and Computer Engineering , 2006.

[18]J. Lee, C. D. CraneIII, “Road Following in an Unstructured Desert Environment Based on the EM (Expectation-Maximization) Algorithm”, SICE-ICASE International Joint Conference ,pp. 2969 - 2974 ,2006.

[19]H. S. Lho, J. W. Kwon, D. Chwa, S. K. Hong,"Vision-based corridor line detection using k-means algorithm” , International Conference on Control, Automation and Systems,PP.1052 – 1056,2007.

[20]http://acoustics.aau.dk/facilities/fac/corridor-3.html

[21]Rafael C. Gonzalez, Richard E. Woods: “Segmentation, Digital image processing”, (Pearson Prentice Hall, 3rd edition, 2008).

[22]G. Hamarneh, K. Althoff, R. Abu-Gharbieh , “Automatic Line Detection”, Project Report for the Computer Vision Course , By Image Analysis Group , Department of Signals and Systems, Chalmers University of Technology ,September 1999.

[23]R. O. Duda, P. E. Hart, “Use of the Hough transformation to detect lines and curves in pictures”, Communications of the ACM, vol. 15, January 1972, pp. 11–15.

[24]N. Aggarwal, W. C. Karl: “Line detection in image through regularized Hough transforms”, IEEE Transactions in Image Processing, vol. 15, no. 3, Mar. 2006.

[25]J. C. Russ , The image processing handbook ,CRC Press, Taylor & Francis Group, 5th ed., 2007.

[26]http://www.berkshireflooring.co.uk/casestudies.asp

[27]http://thingsinjars.com/post/112/office-corridor/

International Journal of Image, Graphics and Signal Processing (IJIGSP)