Star identification algorithm for uncalibrated, wide Fov cameras

Abstract

A novel method is proposed for star identification via uncalibrated cameras with wide fields of view (FOVs). In this approach some of the triangles created by the stars in the FOV are selected for pattern recognition. The triangles are selected considering the sensitivity of their interior angles to the calibration error. The algorithm is based on the intersection between sets of triangles that are found in the database for each selected triangle of the image. By this method, most of the image stars contribute to pattern recognition and thereby it is very robust against the noise and the calibration error. The algorithm is performed on 150 night sky images, which are taken by an uncalibrated camera in FOV of 114° ± 12° with a success rate of 94% and no false positives. Based on the identification approach, an adaptive method is also developed for calibrating and obtaining the projection function of an uncalibrated camera.