{'fraction_non_alphanumeric': 0.010183299389002037, 'fraction_numerical': 0.0, 'mean_word_length': 4.9939024390243905, '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}}
Signature-based image identification

The use of digital images and video is growing on the Internet and on consumer devices. Digital images and video are easy to manipulate, but this ease of manipulation makes tampering with digital content possible. Examples of the misuse of digital content include violating copyrights of the content and tampering with important material such as contents of video surveillance. In this paper we present an algorithm that extracts a binary signature from an image. This approach can be used to search for possible copyright violations by finding images with signatures close to that of a given image. The experimental results show that the algorithm can be very effective in helping users to retrieve sets of almost identical images from large collections of images. The signature can also be used for tamper detection. We will show that the signatures we extract are immune to quantization errors that result from compression and decompression.