{'fraction_non_alphanumeric': 0.015544041450777202, 'fraction_numerical': 0.0012953367875647669, 'mean_word_length': 5.663793103448276, '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}}
Rotational invariant similarity measurement for content-based image indexing

We propose a similarity matching technique for contents based image retrieval. The proposed technique is invariant from rotated images. Since image contents for image indexing and retrieval would be arbitrarily extracted from still image or key frame of video, the rotation invariant property of feature description of image is important for general application of contents based image indexing and retrieval. In this paper, we propose a rotation invariant similarity measurement in cooperating with texture featuring base on HVS. To simplify computational complexity, we employed hierarchical similarity distance searching. To verify the method, experiments with MPEG-7 data set are performed.