{'fraction_non_alphanumeric': 0.013975155279503106, 'fraction_numerical': 0.0, 'mean_word_length': 5.576530612244898, '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}}
A Novel Image Alignment Algorithm Based on Rotation-Discriminating Ring-Shifted Projection for Automatic Optical Inspection

This paper proposes a novel image alignment algorithm based on rotation-discriminating ring-shifted projection for automatic optical inspection. This new algorithm not only identifies the location of the template image within an inspection image but also provides precise rotation information during the template-matching process by using a novel rotation estimation scheme, the so-called ring-shifted technique. We use a two stage framework with an image pyramid searching technique for realizing the proposed image alignment algorithm; in the first stage, the similarity based on hybrid projection transformation with the image pyramid searching technique is employed for quick selection and location of the candidates in the inspection image. In the second stage, the rotation angle of the object is estimated by a novel ring-shifted technique. The estimation is performed only for the most likely candidate which is the one having the highest similarity in the first stage. The experimental results show that the proposed method provides accurate estimation for template matching with arbitrary rotations and is applicable in various environmental conditions.