{'fraction_non_alphanumeric': 0.019736842105263157, 'fraction_numerical': 0.001644736842105263, 'mean_word_length': 5.6923076923076925, '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}}
Multiscale medial description of gray-scale image structure

The computation of structural descriptions of objects in images can contribute to many image analysis tasks including measurement, registration, and object formation and identification. Edge-based structural descriptions fail to support the creation of coherent objects. Medial descriptions provide better support for object formation and measurement. We demonstrate an artificial visual system that uses outputs of Gaussian derivative filters to infer a multiscale medial axis (MMA) in 2-D grayscale images. Properties of the MMA are illustrated.