{'fraction_non_alphanumeric': 0.009149130832570906, 'fraction_numerical': 0.0, 'mean_word_length': 5.39766081871345, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A novel technique for estimating intrinsic camera parameters in geometric camera calibration

In the field of machine vision, camera calibration refers to the experimental determination of a set of parameters which describe the image formation process for a given analytical model of the machine vision system. A complete set of calibration parameters includes both the intrinsic parameters that describe the lens-camera-frame grabber combination as well as the extrinsic parameters that relate the position and orientation of the camera to a fixed reference frame. In this paper, a new approach towards camera calibration is proposed in which the image center and focal length are calculated independently of the lens distortion. A practical experiment was conducted to validate this study. The experimental results show that this technique has the potential to improve calibration accuracy. The paper also compares the results obtained using the new technique and those obtained by applying the systematic camera calibration algorithm proposed by Heikkila using the same experimental set up.