Extracting Depth Information Using a Correlation Matching Algorithm

Mahmoud Abdelhamid, Jeffery Beers, Mohammed Omar

Clemson University International Center for Automotive Research CU-ICAR, Greenville, USA..

DOI: 10.4236/jsea.2012.55036                

Abstract

This manuscript presents a modified algorithm to extract depth information from stereo-vision acquisitions using a correlation based approaches. The main implementation of the proposed method is in the area of autonomous Pick & Place, using a robotic manipulator. Current vision-guided robotics is still based on a priori training and teaching steps, and still suffers from long response time. This study uses a stereo triangulation setup where two Charged Coupled Devices CCDs are arranged to acquire the scene from two different perspectives. The study discusses the details to calculate the depth using a correlation matching routine which programmed using a Square Sum Difference SSD algorithm to search for the corresponding points from the left and the right images. The SSD is further modified using an adjustable Region Of Interest ROI along with a center of gravity based calculations. Furthermore, the two perspective images are rectified to reduce the required processing time. The reported error in depth using the modified SSD method is found to be around 1.2 mm.

Keywords

Stereo-Vision; Depth; Passive Triangulation; Pick and Place

Conflicts of Interest

The authors declare no conflicts of interest.

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