V. V. Korotaev, T. S. Djamiykov, V. N. Hoang, S. N. Yaryshev

Read the full article 
Article in Russian

The paper deals with the structural scheme of active stereoscopic system and algorithm of its operation, providing the fast calculation of the spatial coordinates. The system includes two identical cameras, forming a stereo pair, and a laser scanner, which provides vertical scanning of the space before the system by the laser beam. A separate synchronizer provides synchronous operation of the two cameras. The developed algorithm of the system operation is implemented in MATLAB. In the proposed algorithm, the influence of background light is eliminated by interframe processing. The algorithm is based on precomputation of coordinates for epipolar lines and corresponding points in stereoscopic image. These data are used to quick calculation of the three-dimensional coordinates of points that form the three-dimensional images of objects. Experiment description on a physical model is given. Experimental results confirm the efficiency of the proposed active stereoscopic system and its operation algorithm. The proposed scheme of active stereoscopic system and calculating method for the spatial coordinates can be recommended for creation of stereoscopic systems, operating in real time and at high processing speed: devices for face recognition, systems for the position control of railway track, automobile active safety systems.

Keywords: stereoscopic system, image processing, three-dimensional image, laser scanner, corresponding points, epipolar lines

Acknowledgements. The work was partially financially supported by the Government of the Russian Federation (grant 074- U01).

 1.     Machikhin A.S., Kolyuchkin V.Ya., Timashova L.N. Odnokamernaya skaniruyushchaya stereoskopicheskaya sistema dlya rekonstruktsii trekhmernoi struktury ob"ektov [One-scanning system for stereoscopic reconstruction of 3D structure of objects]. Scientific and Technical Journal of Information Technologies, Mechanics and Optics,2007, no. 38, pp. 142–146.
2.     Zuev V.E. Distantsionnoe Opticheskoe Zondirovanie Atmosfery [Remote Optical Sensing of the Atmosphere]. St. Petersburg, Gidrometeoizdat Publ., 1992, 232 p.
3.     Katalog 3D-Skanerov s Podrobnym Opisaniem i Tsenoi [3D-scanners Catalogue with a Detailed Description and Price]. Available at: (accessed 01.07.2014).
4.     Klimanov M.M. Lazernaya triangulyatsionnaya izmeritel'naya sistema [Laser triangulation measurement system]. Materialy XI Nauchnoi Kkonferentsii MGTU "Stankin" po Matematicheskomu Modelirovaniyu i Informatike [Proc. XI Conf. MGTU "STANKIN" on Mathematical Modeling and Computer]. Moscow, MGTU "Stankin" Publ., 2008, pp. 230–232.
5.     Ponomarev S.V. Metodika sravneniya algoritmov stereozreniya pri vosstanovlenii trekhmernoi modeli litsa cheloveka [Comparison methods of stereo vision algorithms for 3D face reconstruction]. Scientific and Technical Journal of Information Technologies, Mechanics and Optics,2013, no. 6 (88), pp. 40–45.
6.     Gutierrez S., Marroquin J.L. Robust approach for disparity estimation in stereo vision. Image and Vision Computing, 2004, vol. 22, no. 3, pp. 183–195. doi:10.1016/j.imavis.2003.08.006
7.     Bleyer M., Gelautz M. A layered stereo matching algorithm using image segmentation and global visibility constraints. ISPRS Journal of Photogrammetry and Remote Sensing, 2005, vol. 59, no. 3, pp. 128–150. doi: 10.1016/j.isprsjprs.2005.02.008
8.     Kim H., Sohn K. 3D reconstruction from stereo images for interactions between real and virtual objects. Signal Processing: Image Communication, 2005, vol. 20, no. 1, pp. 61–75. doi:10.1016/j.image.2004.10.004
9.     Stefano L.D., Marchionni M., Mattocia S. A fast area-based stereo matching algorithm. Image and Vision Computing, 2004, vol. 22, no. 12, pp. 983–1005. doi: 10.1016/j.imavis.2004.03.009
10.Binaghi E., Gallo I., Marino G., Raspanti M. Neural adaptive stereo matching. Pattern Regonition Letters, 2004, vol. 25, no. 15, pp. 1743–1758. doi: 10.1016/j.patrec.2004.07.001
11.Ogale A.S., Aloimonos Y. Shape and the stereo correspondence problem. International Journal of Computer Vision, 2005, vol. 65, no. 3, pp. 147–162. doi: 10.1007/s11263-005-3672-3
12.Yoon S., Park S.-K., Kang S., Kwak Y.K. Fast correlation-based stereo matching with the reduction of systematic errors. Pattern Recognition Letters, 2005, vol. 26, no. 14, pp. 2221–2231. doi: 10.1016/j.patrec.2005.03.037
13.Gruzman I.S., Kirichuk V.S., Kosykh V.P., Peretyagin G.I., Spektor A.A. Tsifrovaya Obrabotka Izobrazhenii v Informatsionnykh Sistemakh [Digital Image Processing in Information Systems]. Novosibirsk, NGTU Publ., 2000, 168 p.
14.Arakantsev K.G., Gorbachev A.A., Serikova M.G. Stereoskopicheskaya sistema kontrolya fakticheskogo polozheniya zheleznodorozhnogo puti [Stereoscopic system for railway track position control]. Izv. vuzov. Priborostroenie, 2013, vol. 56, no. 5, pp. 34–39.

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Copyright 2001-2019 ©
Scientific and Technical Journal
of Information Technologies, Mechanics and Optics.
All rights reserved.