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http://dx.doi.org/10.3745/KIPSTA.2010.17A.4.189

A Robust Marker Detection Algorithm Using Hybrid Features in Augmented Reality  

Park, Gyu-Ho ((주)한울네오텍)
Lee, Heng-Suk ((주)한울네오텍)
Han, Kyu-Phil (금오공과대학교 컴퓨터공학부)
Publication Information
The KIPS Transactions:PartA / v.17A, no.4, 2010 , pp. 189-196 More about this Journal
Abstract
This paper presents an improved marker detection algorithm using hybrid features such as corner, line segment, region, and adaptive threshold values, etc. In usual augmented reality environments, there are often marker occlusion and poor illumination. However, existing ARToolkit fails to recognize the marker in these situations, especially, partial concealment of marker by user, large change of illumination and dim circumstances. In order to solve these problems, the adaptive threshold technique is adopted to extract a marker region and a corner extraction method based on line segments is presented against marker occlusions. In addition, a compensating method, corresponding the marker size and center between registered and extracted one, is proposed to increase the template matching efficiency, because the inside marker size of warped images is slightly distorted due to the movement of corner and warping. Therefore, experimental results showed that the proposed algorithm can robustly detect the marker in severe illumination change and occlusion environment and use similar markers because the matching efficiency was increased almost 30%.
Keywords
Marker Detection; Illumination Change; Adaptive Threshold; Marker Occlusion Problem; Template Matching;
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