{'fraction_non_alphanumeric': 0.013574660633484163, 'fraction_numerical': 0.0, 'mean_word_length': 5.321428571428571, '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}}
Object distance detection using a joint transform correlator

Computer stereo vision makes heavy use of object distance detection. The primary method to detect object distance is to compare two images of the same scene taken from different vantage points. The necessity of comparing two images naturally leads us to investigate optical correlators. Since the Fourier transform, on which optical correlators are based, is lossless, we suppose that distance information encoded in a stereo image pair is preserved through the correlation process. We then try to recover that distance by investigating the location of the correlation peaks. Initial data indicates that we may plausibly extract distance information from a correlation result. However, this data was gathered under very specific and controlled conditions, and further research is necessary to derive a more general result.