{'fraction_non_alphanumeric': 0.012684989429175475, 'fraction_numerical': 0.0, 'mean_word_length': 5.493150684931507, '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}}
Self calibration of a road stereo color vision system using a similarity criterion

In this article, we address the problem of self calibrating an embedded stereoscopic color vision system, by matching interest points, and computing the related fundamental matrix. We propose a new method based on similarity of image areas surrounding automatically detected interest points. We provide some experimental results, and compare these to those obtained with a classical method