title: Color code identification in coded structured light.
abstract: Color code is widely employed in coded structured light to reconstruct the three-dimensional shape of objects. Before determining the correspondence, a very important step is to identify the color code. Until now, the lack of an effective evaluation standard has hindered the progress in this unsupervised classification. In this paper, we propose a framework based on the benchmark to explore the new frontier. Two basic facets of the color code identification are discussed, including color feature selection and clustering algorithm design. First, we adopt analysis methods to evaluate the performance of different color features, and the order of these color features in the discriminating power is concluded after a large number of experiments. Second, in order to overcome the drawback of K-means, a decision-directed method is introduced to find the initial centroids. Quantitative comparisons affirm that our method is robust with high accuracy, and it can find or closely approach the global peak.
authors.affiliation: Shanghai Key Laboratory of Manufacturing Automation and Robotics, School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200072, China.
authors.forename: Xu
authors.initials: X
authors.lastname: Zhang
authors.forename: Youfu
authors.initials: Y
authors.lastname: Li
authors.forename: Limin
authors.initials: L
authors.lastname: Zhu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003116:Color; D003198:Computer Simulation; D005145:Face; D005260:Female; D006225:Hand; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods; D015233:Models, Statistical; D010363:Pattern Recognition, Automated / Q000379:methods