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http://dx.doi.org/10.9717/kmms.2013.16.1.011

3D Model Reconstruction Algorithm Using a Focus Measure Based on Higher Order Statistics  

Lee, Joo-Hyun (금오공과대학교 컴퓨터공학과)
Yoon, Hyeon-Ju (금오공과대학교 컴퓨터공학과)
Han, Kyu-Phil (금오공과대학교 컴퓨터공학과)
Publication Information
Journal of Korea Multimedia Society / v.16, no.1, 2013 , pp. 11-18 More about this Journal
Abstract
This paper presents a SFF(shape from focus) algorithm using a new focus measure based on higher order statistics for the exact depth estimation. Since conventional SFF-based 3D depth reconstruction algorithms used SML(sum of modified Laplacian) as the focus measure, their performance is strongly depended on the image characteristics. These are efficient only for the rich texture and well focused images. Therefore, this paper adopts a new focus measure using HOS(higher order statistics), in order to extract the focus value for relatively poor texture and focused images. The initial best focus area map is generated by the measure. Thereafter, the area refinement, thinning, and corner detection methods are successively applied for the extraction of the locally best focus points. Finally, a 3D model from the carefully selected points is reconstructed by Delaunay triangulation.
Keywords
3D Reconstruction; Shape From Focus; Higher Order Statistics; Focus Measure;
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Times Cited By KSCI : 1  (Citation Analysis)
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