{'fraction_non_alphanumeric': 0.023001095290251915, 'fraction_numerical': 0.0032858707557502738, 'mean_word_length': 5.260273972602739, '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}}
Fusing sonar images for mine detection and classification

An image fusion method is developed for sonar systems that collect multiple images in a single pass. This research builds on our past work with automated detection and classification of sea mines in side-looking sonar imagery. The new method has the following processing step. Each image is processed separately by our automated detection and classification algorithm. Next detections in the images are collated into two general categories: (1) detections appearing in only one image and (2) detections appearing in multiple images. A fuzzy-logic procedure is used to fuse the detections that are common to multiple images. The final 'fused' classifications will fall under two general descriptions: (1) classifications where sufficient mine-like evidence had to be accumulated over multiple images. This fusion process dramatically reduces false alarms.