{'fraction_non_alphanumeric': 0.018214936247723135, 'fraction_numerical': 0.0, 'mean_word_length': 5.7073170731707314, '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}}
Efficient implementation of vector quantization for image retrieval

Vector quantization histogram (VQH) is a content-based image retrieval technique that has high retrieval effectiveness. However, as VQH's image indexing process is highly computationally intensive, it is not ideal as an online system. We propose an efficient image encoding technique to address this issue. Our experimental results show the proposed technique greatly improves the retrieval efficiency of VQH and it also has little adverse effects on VQH's retrieval effectiveness