Design of coded reference labels for indoor optical navigation using monocular camera

We present a machine vision based indoor navigation system. The paper describes a pose estimation of machine vision system by recognizing rotationally independent optimized color reference labels combined with a geometrical camera calibration model, which determines a set of camera parameters. A reference label carries one byte of information, which can be uniquely designed for various values. More than four reference labels are used in the image to calculate the localization coordinates of the system. An algorithm in Matlab has been developed so that a machine vision system can recognize N number of labels at any given orientation. In addition, a one channel color technique is applied in segmentation process, due to this technique the number of segmented image components is reduced significantly, limiting the memory storage requirement and processing time. The algorithm for pose estimation is based on direct linear transformation (DLT) method with a set of control reference labels in relation to the camera calibration model. From the experiments we concluded that the pose of the machine vision system can be calculated with relatively high precision, in the calibrated environment of reference labels.