Correcting the Geometry and Color of Digital Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Region Snake-Based Segmentation Adapted to Different Physical Noise Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Numerical Recipes in C++: the art of scientific computing
Numerical Recipes in C++: the art of scientific computing
Summed-area tables for texture mapping
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Marker Tracking and HMD Calibration for a Video-Based Augmented Reality Conferencing System
IWAR '99 Proceedings of the 2nd IEEE and ACM International Workshop on Augmented Reality
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Semiautomatic color checker detection in distorted images
SPPRA '08 Proceedings of the Fifth IASTED International Conference on Signal Processing, Pattern Recognition and Applications
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We present an algorithm to detect and track color calibration charts in images robustly. A model of the calibration chart describes the geometry of the chart regions by polygons along with the related reference colors. A homography maps the model into the image and an optimizer adapts the mapping parameters to align the model regions to the chart in the image. We propose a cost function that evaluates the quality of model alignment based on color statistics and an efficient method to extract color statistics in polygonal image regions using the integral image. The algorithm measures the colors of the chart in the image and determines correction parameters. Without loss of generality, we describe the method using the X-Rite ColorChecker Classic as a typical chart. Experiments show the robustness to noise and blur and the real-time capability of the system.