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This paper presents a proposal for the automation of the camera calibration process, locating and measuring image points in coded targets with sub-pixel precision. This automatic technique helps minimize localization errors, regardless of camera orientation and image scale. To develop this technique, several types of coded targets were analyzed and the ARUCO type was chosen due to its simplicity, ability to represent up to 1024 different targets and availability of source code implemented with the OpenCV library. ARUCO targets were generated and two calibration sheets were assembled to be used for the acquisition of images for camera calibration. The developed software can locate targets in the acquired images and it automatically extracts the coordinates of the four corners with sub-pixel accuracy. Experiments were conducted with real data showing that the targets are correctly identified unless excessive noise or fragmentation occurs mainly in the outer target square. The results with the calibration of a low cost camera showed that the process works and that the measurement accuracy of the corners achieves sub-pixel precision.

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA