FPGA based Relative Distance Measurement using Stereo Vision Technology
Commenced in January 2007
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FPGA based Relative Distance Measurement using Stereo Vision Technology

Authors: Manasi Pathade, Prachi Kadam, Renuka Kulkarni, Tejas Teredesai

Abstract:

In this paper, we propose a novel concept of relative distance measurement using Stereo Vision Technology and discuss its implementation on a FPGA based real-time image processor. We capture two images using two CCD cameras and compare them. Disparity is calculated for each pixel using a real time dense disparity calculation algorithm. This algorithm is based on the concept of indexed histogram for matching. Disparity being inversely proportional to distance (Proved Later), we can thus get the relative distances of objects in front of the camera. The output is displayed on a TV screen in the form of a depth image (optionally using pseudo colors). This system works in real time on a full PAL frame rate (720 x 576 active pixels @ 25 fps).

Keywords: Stereo Vision, Relative Distance Measurement, Indexed Histogram, Real time FPGA Image Processor

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1055427

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References:


[1] S. Birchfield, C. Tomasi, "Depth Discontinuties by Pixel-to- Pixel Stereo", International Journal of Computer Vision, Vol. 35(3), pp. 269- 293, (1999).
[2] F. Tombari, S. Mattoccia, L. Stefano, E. Addimanda, "Near real-time stereo based on effective cost aggregation", 19th International Conference on Pattern Recognition, pp. 1-4, (2008).
[3] L. Wang, M. Liao, G. Minglun, Y. Ruigang, "High quality real-time Stereo using Adaptive Cost aggregation and Dynamic Programming", Proceedings of the Third International Symposium on 3D Data Processing, Visualization, and Transmission, pp. 798-805, (2006).
[4] Q. Yang, C. Engels, A. Akbarzadeh, "Near Real-time Stereo for Weakly- Textured Scenes", British Machine Vision Conference, (2008).