A Density-Based Clustering Color Consistency Method for 3D Object Reconstruction

• Main Authors: Yu-Ching Lu, 呂宥瑾
• Other Authors: Sheng-Fuu Lin
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/24888197886872449896

碩士 === 國立交通大學 === 電機與控制工程系所 === 96 === A voxel-based approach for 3D object reconstruction is used in this thesis, and there are four steps in the process of a voxel-based 3D reconstruction system. In the first step, the camera is calibrated, and the purpose of camera calibration is to acquire the intrinsic and extrinsic parameters of the camera. Second, image segmentation is executed to extract object from background. Third, a 3D model is built, and the coordinates and colors information of a large amount of surface points of the object are determined. The third step includes two sub-steps that are voxel visibility and color consistency, and color consistency is the main issue of this thesis. Finally, a reconstructed 3D object is displayed by computer language VC++ with OpenGL libraries in the fourth step. So far, generally speaking, there are three different methods for implementing color consistency, and these three methods are single threshold method, histogram method and adaptive threshold method. A new color consistency method by using the density-based clustering method is proposed in the thesis, and the proposed method is compared with the other three color consistency methods. According to the experimental results, the proposed method can eliminate the unnecessary voxels and determine the true colors of voxels very well.