{'fraction_non_alphanumeric': 0.01364522417153996, 'fraction_numerical': 0.0, 'mean_word_length': 5.119047619047619, '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}}
Comparative Study of Hu Moments and Zernike Moments in Object Recognition

There are lots of ways to perform object recognition. This paper is part of a project studying object recognition. The project is intended as a starting point to further learning about object recognition. Therefore, moment invariants are studied as a good starting point. Hu moment invariant methods and Zernike moment invariant methods are implemented and compared. Zernike moment invariants are shown to outperform Hu moment invariants.