VELOCITY MEASUREMENT BASED ON IMAGE BLUR

This work gathers elements for the study and analysis of the main problems and difficulties inherent to the implementation of a device for inspection of a speedometer of automotive vehicles, in order to meet the foreseen Brazilian legislation which defines the maximum allowed error for speed-meters of ± 5km/h for speeds up to 100km/h and ± 5% for speeds above 100km/h. From this study, a new non contact method based on image analysis, specifically the blur effect, is proposed. In the method, the speed of the target surface is determined by analyzing the characteristics and regularities contained in a single blurred image. Using a device that simulates the soil movement, a CCD camera and a frame grabber, images of the moving asphalt surface are acquired. The information of speed is then determined, through the analysis of the regularities contained in the dynamic image due to the blur effect. The necessary results for the inspection are achieved successfully, with precision below 5%. The developed and evaluated technique demonstrates, through a device that simulates the asphalt in movement, a precision of 0,8% in a range of speeds from 0 to 20km/h, 1,5% in a range of speeds from 20km/h to 60km/h and 2,5% in a range of speeds from 60km/h to 80km/h. Finally, it was investigated the preponderant factors which have limited the errors in this order of magnitude.

[1]  N. H. C. Yung,et al.  A Novel Algorithm for Estimating Vehicle Speed from Two Consecutive Images , 2007, 2007 IEEE Workshop on Applications of Computer Vision (WACV '07).

[2]  Gianluca Casarosa,et al.  Measurement system based on a high-speed camera and image processing techniques for testing of spacecraft subsystems , 2005, International Congress on High-Speed Imaging and Photonics.

[3]  P. Anandan,et al.  A computational framework and an algorithm for the measurement of visual motion , 1987, International Journal of Computer Vision.

[4]  Wilfried Enkelmann,et al.  Investigations of multigrid algorithms for the estimation of optical flow fields in image sequences , 1988, Comput. Vis. Graph. Image Process..

[5]  Huei-Yung Lin,et al.  Motion blur removal and its application to vehicle speed detection , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[6]  David J. Fleet Measurement of image velocity , 1992 .

[7]  Escola Brasileira de Administração Pública. Curso de Plan Regional,et al.  Departamento Nacional de Estradas de Rodagem , 1955 .

[8]  Stefano Soatto,et al.  Scene and Motion Reconstruction from Defocused and Motion-Blurred Images via Anisotropic Diffusion , 2004, ECCV.

[9]  Rangachar Kasturi,et al.  Machine vision , 1995 .

[10]  Ellen C. Hildreth,et al.  Measurement of Visual Motion , 1984 .

[11]  Allen M. Waxman,et al.  Contour Evolution, Neighborhood Deformation, and Global Image Flow: Planar Surfaces in Motion , 1985 .

[12]  E H Adelson,et al.  Spatiotemporal energy models for the perception of motion. , 1985, Journal of the Optical Society of America. A, Optics and image science.

[13]  William B. Thompson,et al.  Disparity Analysis of Images , 1980, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[14]  F. Glazer Hierarchical Motion Detection , 1987 .

[15]  A. Marchewka,et al.  Motion analysis for image sequence coding , 2006 .

[16]  Eric Paquette,et al.  Computer graphics and image processing as an introductory course , 2004 .

[17]  K. Kobayashi,et al.  Absolute speed estimation from sequential frames of omni-directional image , 2003, SICE 2003 Annual Conference (IEEE Cat. No.03TH8734).

[18]  Daniel J. Dailey,et al.  Roadside camera motion detection for automated speed measurement , 2002, Proceedings. The IEEE 5th International Conference on Intelligent Transportation Systems.

[19]  Shree K. Nayar,et al.  Motion deblurring using hybrid imaging , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[20]  Hans-Hellmut Nagel,et al.  Displacement vectors derived from second-order intensity variations in image sequences , 1983, Comput. Vis. Graph. Image Process..

[21]  Claude L. Fennema,et al.  Velocity determination in scenes containing several moving objects , 1979 .