{'fraction_non_alphanumeric': 0.022481265611990008, 'fraction_numerical': 0.0, 'mean_word_length': 5.293193717277487, '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}}
Randomized Hough Transform (RHT) in Engineering Drawing Vectorization System

When the data is processed from the digitized drawThis paper presents how the recently presented Randomized IIough Transform (RHT) method can be used as a part of an engineering drawing vectorization system. The RHT algorithm is capable of recognizing and fitting straight line segments, circles, arcs and conic curve segments, in preprocessed images (eg. after noise removal, void filling). The thinning phase is not necessarily needed. The RHT method is based on the fact that a single parameter space point representing a curve in the image space, can be determined uniquely with a pair, triple, or generally n-tuple of points from the image. These point tuples can be chosen randomly and Hough transform like accumulation is used to detect curve parameters. Preliminary computer experiments using engineering drawings which contain line segments, circles with variable radius and other data, have shown that RIIT has reasonable performance in the line extraction task. It avoids problems which are faced with standard Hough transform (HT) techniques such as low parameter resolution, high storage and time complexities.