{'fraction_non_alphanumeric': 0.018854748603351956, 'fraction_numerical': 0.002094972067039106, 'mean_word_length': 5.176724137931035, '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}}
Fast recognition method for metallic topographies by the three-color selective stereo gradient method

A machine-vision system for real-time classification of moving objects with highly reflective metallic surfaces and complex 3D-structures is presented. As an application example of our Three-Color Selective Stereo Gradient Method (Three-Color SSGM) a classification system for the three main coin denominations of Euro coins is presented. The coins are quickly moving in a coin validation system. The objective is to decide only from comparison of measured 3D-surface properties with characteristic topographical data stored in a database whether a coin belongs to one of the reference classes or not. Under illumination of a three-color LED-ring a single image of the moving coin is captured by a CCD-camera. Exploiting the spectral properties of the illumination sources, which correspond to the special spectral characteristics of the camera, three independent subimages can be extracted from the first. Comparison between these subimages leads to a discrimination between a coin with real 3D-surface and a photographic image of a coin of the same type. After the coin has been located and segmented, grey value based rotation and translation invariant features are extracted from a normalized image. In combination with template matching methods, a coin can be classified. Statistical classification results will be reported.