Images Of Checkerboard Pattern Research Articles

Fast approach to checkerboard corner detection for calibration

To reduce accuracy lost in the calibration process for high-precision optical systems using interferometry, an approach is proposed to detect checkerboard corners based on the level set evolution principle. Compared with existing corner detection methods, no image gradients are required for segmentation of checkerboard patterns. It has the capability of doing corner detection for the images acquired under more complex imaging environments, like underwater, low-contrast, blurred, and heavily distorted images. In addition, no iteration is required in the level set evolution procedure, and a fast speed is achieved. In this implementation, the grids that consist of a checkerboard pattern are first found as level set curves by segmenting the checkerboard pattern image. Then, noting that checkers might be recognized as quadrangles, the four corners of a quadrangle can be located by checking the varying of points of its boundary in slope. Alternatively, they also could be located according to the maximal distance at specific orientations between a point and the center of the closed curve. Finally, several experiment results are presented to validate the proposed approach and to demonstrate its robustness and correctness.

Wavefront fitting and comparison of camera aberrations using Zernike circle polynomials

Zernike polynomials are in widespread use for wavefront analysis because of their representation of classical aberrations. This paper presents a method to investigate wavefront aberrations which does not require complicated and expensive wavefront sensors. Images of checkerboard pattern are captured using mobile phone cameras, CCTV camera, Firewire camera, Handy cam and Stereo camera and wavefront is constructed using displacement in the grid corners of checkerboard patterns. This wavefront is fitted into Zernike circle polynomials and Zernike coefficients are computed using Gaussian elimination method. The computed Zernike polynomials and Zernike coefficients are further utilized to compare the aberrations of different cameras. The experiment and simulations confirm that displacement in the grid corners of the checkerboard pattern can be treated as a wavefront and fitted to Zernike polynomials. Stereo camera is also investigated for both raw and rectified set of images.

A New Solution for Camera Calibration and Real-Time Image Distortion Correction in Medical Endoscopy–Initial Technical Evaluation

Medical endoscopy is used in a wide variety of diagnostic and surgical procedures. These procedures are renowned for the difficulty of orienting the camera and instruments inside the human body cavities. The small size of the lens causes radial distortion of the image, which hinders the navigation process and leads to errors in depth perception and object morphology. This article presents a complete software-based system to calibrate and correct the radial distortion in clinical endoscopy in real time. Our system can be used with any type of medical endoscopic technology, including oblique-viewing endoscopes and HD image acquisition. The initial camera calibration is performed in an unsupervised manner from a single checkerboard pattern image. For oblique-viewing endoscopes the changes in calibration during operation are handled by a new adaptive camera projection model and an algorithm that infer the rotation of the probe lens using only image information. The workload is distributed across the CPU and GPU through an optimized CPU+GPU hybrid solution. This enables real-time performance, even for HD video inputs. The system is evaluated for different technical aspects, including accuracy of modeling and calibration, overall robustness, and runtime profile. The contributions are highly relevant for applications in computer-aided surgery and image-guided intervention such as improved visualization by image warping, 3-D modeling, and visual SLAM.

Recognition and location of the internal corners of planar checkerboard calibration pattern image

The recognition and location of the internal corners of a planar checkerboard calibration pattern image is very important to camera calibration. An effective approach is proposed to automatically recognize and locate the internal corners of the planar checkerboard calibration pattern image based on the characteristics of local intensity and the grid line architecture of the planar checkerboard pattern image. The proposed procedure consists of the detection of image corners, the recognition of the corners at the intersections of black and white squares and the recognition of the corners at the intersections of two groups of grid lines. Experiments show that compared with the commonly used interactive method, the proposed approach obviously reduces the time cost for camera calibration, speeds up calibration process and is especially adapted for automatic calibration based on multiple images.