Multi-view 3D reconstruction and modeling of the unknown 3D scenes using genetic algorithms

Nonlinear optimization considering target feature points for bitelecentric camera calibration: experimental study

The telecentric camera has found extensive application in microscopy imaging due to its remarkable attributes of maintaining constant magnification and minimal distortion within its depth of field. In telecentric imaging technology, the accuracy of measurements frequently hinges upon the calibration precision of the telecentric camera. In real-world scenarios, the shallow depth of field characteristic of telecentric cameras often leads to out-of-focus targets during the capturing process, which in turn results in the inability to accurately extract pixel coordinates of feature points, making it difficult for optimization algorithms to converge to the optimal value. We propose a nonlinear optimization algorithm based on pixel coordinates of optimized feature points for bitelecentric cameras. Incorporating pixel coordinates into the optimization process yields the theoretically optimal solution based on bitelecentric camera model. The obtained pixel coordinates are used for second initial value estimation, followed by the optimization of all parameters. Compared to existing methods, the proposed approach significantly reduces reprojection errors under both blurry and clear target conditions. Experimental results demonstrate superior performance in processing blurry defocused images.

Constrained nonlinear optimization method for accurate calibration of a bi-telecentric camera in a three-dimensional microtopography system

Telecentric cameras are widely used in the field of microscopic imaging because of their constant magnification and tiny distortion in the depth of field. Camera calibration has always been a key step in the field of computer vision. Usually, the precise parameters of the telecentric camera are obtained by nonlinear optimization; however, the randomness of the optimization algorithm without proper constraints will cause the results to be inconsistent with reality. Existing studies paid little attention to this issue; therefore, we show a reliable optimization approach for the bi-telecentric camera in a structured illumination three-dimensional microtopography measurement system. In this method, the distortion-free camera parameters are solved through a closed-form solution. Then a nonlinear optimization algorithm with constraining the world coordinates of the precise calibration target is proposed to refine the global parameters, leading to the calibration results being more accurate and authentic. The real experiments are conducted to verify the feasibility of the proposed method. The comparative experiments with the exiting approach are then carried out, manifesting that the proposed method enjoys advantages in terms of both reprojection error and operating efficiency. Additionally, the average offset of the world coordinates on the calibration target derived from the proposed method verifies its effectiveness and reasonability.

Reconstruction and optimization of the 3D geometric anatomy structure model for subject-specific human knee joint based on CT and MRI images

BACKGROUND:

Nowadays, the total knee arthroplasty (TKA) technique plays an important role in surgical treatment for patients with severe knee osteoarthritis (OA). However, there are still several key issues such as promotion of osteotomy accuracy and prosthesis matching degree that need to be addressed.

OBJECTIVE:

It is significant to construct an accurate three-dimensional (3D) geometric anatomy structure model of subject-specific human knee joint with major bone and soft tissue structures, which greatly contributes to obtaining personalized osteotomy guide plate and suitable size of prosthesis.

METHODS:

Considering different soft tissue structures, magnetic resonance imaging (MRI) scanning sequences involving two-dimensional (2D) spin echo (SE) sequence T1 weighted image (T1WI) and 3D SE sequence T2 weighted image (T2WI) fat suppression (FS) are selected. A 3D modeling methodology based on computed tomography (CT) and two sets of MRI images is proposed.

RESULTS:

According to the proposed methods of image segmentation and 3D model registration, a novel 3D knee joint model with high accuracy is finally constructed. Furthermore, remeshing is used to optimize the established model by adjusting the relevant parameters.

CONCLUSIONS:

The modeling results demonstrate that reconstruction and optimization model of 3D knee joint can clearly and accurately reflect the key characteristics, including anatomical structure and geometric morphology for each component.

A Single Image 3D Reconstruction Method Based on a Novel Monocular Vision System

Three-dimensional (3D) reconstruction and measurement are popular techniques in precision manufacturing processes. In this manuscript, a single image 3D reconstruction method is proposed based on a novel monocular vision system, which includes a three-level charge coupled device (3-CCD) camera and a ring structured multi-color light emitting diode (LED) illumination. Firstly, a procedure for the calibration of the illumination's parameters, including LEDs' mounted angles, distribution density and incident angles, is proposed. Secondly, the incident light information, the color distribution information and gray level information are extracted from the acquired image, and the 3D reconstruction model is built based on the camera imaging model. Thirdly, the surface height information of the detected object within the field of view is computed based on the built model. The proposed method aims at solving the uncertainty and the slow convergence issues arising in 3D surface topography reconstruction using current shape-from-shading (SFS) methods. Three-dimensional reconstruction experimental tests are carried out on convex, concave, angular surfaces and on a mobile subscriber identification module (SIM) card slot, showing relative errors less than 3.6%, respectively. Advantages of the proposed method include a reduced time for 3D surface reconstruction compared to other methods, demonstrating good suitability of the proposed method in reconstructing surface 3D morphology.