On stereo correspondence estimation: a spiral search algorithm

Md. Abdul Mannan Mondal; Md. Haider Ali

doi:10.1117/12.913526

1 October 2011 On stereo correspondence estimation: a spiral search algorithm

Md. Abdul Mannan Mondal, Md. Haider Ali

Proceedings Volume 8285, International Conference on Graphic and Image Processing (ICGIP 2011); 82857H (2011) https://doi.org/10.1117/12.913526
Event: 2011 International Conference on Graphic and Image Processing, 2011, Cairo, Egypt

Abstract

This paper introduces a searching algorithm called "spiral searching" for computing stereo correspondence or disparity of the stereo images. The method is based on computation of the minimum window cost among the contributions of the windows bounded in the range from minimum depth of spiral to maximum depth of spiral. This algorithm can estimate stereo correspondence of a pair of images concurrently two dimensionally and it avoids false matching causes to increase the accuracy and requires minimum executing time than the traditional one dimensional searching strategies. This method first calculates two window costs - one in positive x-direction and another in negative y-direction using the same distance from the origin. Minimum of the two window costs and coordinate distances are considered for second calculation. Secondly, following the same way another two window costs are calculated - one in negative x-direction and another in positive y-direction using the same distance from the origin. Minimum of the two window costs and coordinate distances are compared to the previous two window costs. This process is bounded from minimum depth of spiral to maximum depth of spiral. Experimental result demonstrates that the visual quality of the output image is very close to ground truth image.

Citation Download Citation

Md. Abdul Mannan Mondal and Md. Haider Ali "On stereo correspondence estimation: a spiral search algorithm", Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82857H (1 October 2011); https://doi.org/10.1117/12.913526

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KEYWORDS

Image segmentation

Image processing algorithms and systems

Image quality

Visualization

Computing systems

Machine vision

3D image processing

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