{'fraction_non_alphanumeric': 0.01982651796778191, 'fraction_numerical': 0.0, 'mean_word_length': 5.412698412698413, '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}}
Colour image retrieval based on the hypergraph combined with a weighted adjacent structure

Content-based image retrieval (CBIR) is a research hotspot. To improve the performance of a CBIR system, especially the retrieval accuracy, this work proposes a method that uses a soft hypergraph combined with a weighted adjacent structure (WAS) to retrieve images. In this method, the similarities between images are computed and a similarity matrix is constructed by a conjoined colour difference histogram and micro-structure descriptor method. Furthermore, a novel WAS and a soft hypergraph model are utilised to further improve the retrieval precision. The proposed method is compared with other methods in several datasets. Experimental results manifest the performance and robustness of this proposed method.