Key Technologies For 3D Reconstruction Under Uneven Illumination

3D Reconstruction has a wide application in virtual reality,augmented reality,computer graphics,CAD,animation,computer vision,medical image reconstruction,digital media,reverse engineering,digital museum and digital city etc,it has been a hot research topic in computer vision for many years.The image captured from camera is the basic data for 3D reconstruction in real application.Because of the uneven envi-ronmental illumination or surface reflectance of objects,the captured images are often bad.Uneven illumination is one of the key and fundamental problems in 3D recon-struction.Thus this dissertation mainly focus on the study of some key technologies for 3D reconstruction under uneven illumination,for example,the influence of uneven illumination on camera calibration,3D reconstruction of reflectance object,seamless texture mapping of 3D model etc..The research work and main innovations in this dissertation are as follows:(1)To improve the precision of calibration under uneven illumination,by analyz-ing the influence of uneven illumination on corner detection,sub-pixel optimization,calibration board identification and camera parameters optimization etc.systematical-ly,an high precision camera calibration method based on checkerboard pattern under uneven illumination is proposed.First,to improve the precision of corner detection,a Harris corner detection method based on color constancy is proposed,the improved algorithm is very effective even for high dynamic range image.For the optimization of sub-pixel detection,an algorithm based on the heuristic knowledge of chessboard and the quadric surface fitting is proposed.For better calibrated board identification,a new form of chessboard with a center circle is designed,by combining the location of the center circle and mesh Delaunay,the calibrated board can be identified effec-tively under uneven illumination.Finally,to overcome the inconsistency of radial lens distortion,an optimized algorithm is proposed to reduce the radial lens distortion for uneven illumination.Compared with other methods,experiments showed that the pro-posed method achieved stable and accurate calibration under complicated illumination conditions.(2)By analyzing the influence of incorrect exposure on phase recovery and the phase error introduced by saturation,an algorithm is proposed for phase recovery and 3D reconstruction based on high dynamic range imaging technologies.Unlike existing methods that use grey values to calculate phase angle,the proposed method uses E val-ues,which are the recovered irradiance from multiple exposure images,to calculate the phase angle for specular surfaces.First,a sequence of fringe images with multiple ex-posures is captured.Then,the E value maps can be rebuilt by recovering them for every pixel at each shifting step.Finally,the phase angle for each pixel is recovered from the E value.By recovering the E value from multi-exposure images,the camera’s dynamic range is enlarged and the effect of random noise is suppressed.Thus,the accuracy of phase recovery is improved.Compared with traditional phase shifting methods based on HDR imaging,the proposed method takes into account not only grey values under one exposure,but also grey values under other exposures.Experimental results show that the proposed method improves the phase recovery accuracy and achieve good re-sults for the 3D reconstruction of dark and specular surfaces.For different objects,experiments showed that the proposed method recovered the phase angle accurately based on irradiance maps,and achieved good 3D reconstruction effects compared with other HDR methods.(3)For the texture mapping of reconstructed 3D models,the texture images are captured from different views and distances,thus the images are often suffered from color reflection and bad illumination.To achieve seamless texture mapping,an algo-rithm based on multi-resolution decomposition and fusion is proposed for 3D recon-struction.Firstly,a series of image sets are produced by analyzing the visibility of triangular facets,and the image sets are clustered and segmented into a number of op-timal reference texture patches.Secondly,the generated texture patches are sequenced to create a rough texture map,then a weighting process is adopted to reduce the color discrepancies between adjacent patches.Finally,multi-resolution decomposition and fusion technique are used to generate the transition section and eliminate the bound-ary effect.Experiments show that the proposed algorithm is effective and practical in obtaining high quality 3D texture mapping for 3D reconstruction.Compared with traditional methods,it maintains the texture clarity while eliminates the color seam-s,besides,it also supports 3D texture mapping for big data application.Compared with optimal selection methods etc.,experiments showed that,even large color differ-ence exists,the proposed method achieved seamless texture mapping and image details maintenanceIn brief,the innovative work in this dissertation achieves good effects for 3D re-construction under uneven illumination.Due to the complexity of 3D reconstruction technologies and the diversity of real objects,the proposed methods are still limited for highly reflectance surface especially for mirror-like surfaces.