Abstract
In order to perform precise identification and location of artificial coded targets in natural scenes, a novel design of circle-based coded target and the corresponding coarse-fine extraction algorithm are presented. The designed target separates the target box and coding box totally and owns an advantage of rotation invariance. Based on the original target, templates are prepared by three geometric transformations and are used as the input of shape-based template matching. Finally, region growing and parity check methods are used to extract the coded targets as final results. No human involvement is required except for the preparation of templates and adjustment of thresholds in the beginning, which is conducive to the automation of close-range photogrammetry. The experimental results show that the proposed recognition method for the designed coded target is robust and accurate.
Highlights
Close-range photogrammetry (CRP) is a key technique for determining the three-dimensional (3D) geometry of a physical object by analyzing and measuring features appearing in twodimensional photographs of the object and has found many diverse applications in the fields of industry, architecture, automotive, as well as virtual reality technique (Luhmann, 2010)
In order to correctly reconstruct the corresponding relationship between 2D image coordinates and 3D world coordinates, it is critical to accurately extracting the image coordinates of feature points (Feng et al, 2002)
In order to overcome the shortages of circle-based coded target extraction methods mentioned above, this paper presents a novel design of circle-based coded target, including feature point coordinate and feature point serial number simultaneously
Summary
Close-range photogrammetry (CRP) is a key technique for determining the three-dimensional (3D) geometry of a physical object by analyzing and measuring features appearing in twodimensional photographs of the object and has found many diverse applications in the fields of industry, architecture, automotive, as well as virtual reality technique (Luhmann, 2010). In order to overcome the shortages of circle-based coded target extraction methods mentioned above, this paper presents a novel design of circle-based coded target, including feature point coordinate and feature point serial number simultaneously. This target design can fulfill the need of being detected and recognized accurately, and could be located from farther distance and wider angle, especially in complex environment. This method has three main stages: 1) template preparation by a set of geometric transformations based on the original target; 2) shapebased template matching; and 3) center points location based on region-growing and false results removal by parity-check. The target is almost the half size of A4 paper and it can be scaled in equal proportion if necessary
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