{'fraction_non_alphanumeric': 0.016238159675236806, 'fraction_numerical': 0.0, 'mean_word_length': 5.166666666666667, '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}}
An improved method of computing scale-orientation signatures

Scale-Orientation Pixel Signatures provide a rich description of the neighbourhood around each image pixel. In Computer-Aided Mammography these signatures can be used as feature vectors for the classification of pixels as normal or abnormal. Previous work has focussed on the use of signatures in the classification process. In this paper we explain how signatures are generated and provide a critique of our current approach. We propose alternative methods of signature generation, along with a quantitative measure of signature ‘quality’. We use this measure to compare the performance of our old and new methods and show that the new approach offers a significant advantage.