An artificial intelligence algorithm-based house drawing recognition system for earthquake risk survey

Abstract

Considering the major problems in the earthquake risk survey, the study aims at researching, designing, and building a house drawing recognition system for the earthquake risk survey. Focusing on Optical Character Recognition technology (OCR), together with artificial intelligence algorithms such as text detection based on Differentiable Binarization (DBNet) algorithm, CRNN+CTC algorithm-based image recognition, and image segmentation with K-means algorithm, this paper elaborates on the operation process, technology selection, system design, and application effect of the system. The system shows positive effects on the collection, calibration, and output of census data, which improves the efficiency and quality of earthquake risk surveys.