{'fraction_non_alphanumeric': 0.0273109243697479, 'fraction_numerical': 0.0021008403361344537, 'mean_word_length': 4.746987951807229, '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}}
Similarity measures for pattern matching on-the-fly

Recently, we presented a new OCR-concept [1] for historic prints. The core part is the glyph recognition based on pattern matching with patterns that are derived from computer font glyphs and are generated on-the-fly. The classification of a sample is organized as a search process for the most similar glyph pattern. In this paper, we investigate several similarity measures which are of vital importance for this concept.