{'fraction_non_alphanumeric': 0.01779935275080906, 'fraction_numerical': 0.012944983818770227, 'mean_word_length': 5.316326530612245, '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}}
Moving shadow detection and removal for video-based traffic monitoring

In this paper, a shadow detection and removal framework for a video-based traffic monitoring system is proposed. The proposed framework is able to correctly detect if a video sequence has cast shadows that needs to be removed. Shadow detection results in 90.39% shadow detection rate and 88.71% shadow discrimination rate for different daytime traffic scenes with varying shadow strength. A traffic monitoring system using the proposed shadow removal framework shows improvement on traffic volume and road occupancy parameter extraction accuracy.