{'fraction_non_alphanumeric': 0.014573991031390135, 'fraction_numerical': 0.0, 'mean_word_length': 5.424460431654676, '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}}
Image Matching for Individual Recognition with SIFT, RANSAC and MCL

Monitoring the whale individuals in the ocean is a current problem among conservationists. Biologists often use photos of whale caudal for this problem as it is the most discriminant pattern for distinguishing an individual whale from another, but it often requires laborious visual analysis. There was a challenge announced in the SeaCLEF of LifeCLEF campaign for automatic whale individual recognition based on visual contents. We elaborated a solution to compare the photos of individuals by SIFT features (as simple image representation) with spatial consistency refinement method RANSAC (based on a rotation and scale transformation model). After determining the similarity of every pair, to discover the wrong similarity values and correct them, a clustering method was applied on the similarity graph of the dataset.