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Journal of Graphics ›› 2022, Vol. 43 ›› Issue (4): 729-735.DOI: 10.11996/JG.j.2095-302X.2022040729

• BIM/CIM • Previous Articles     Next Articles

Research on recognition method of overlapped characters in construction drawings based on adaptive scale edge feature

  

  1. 1. School of Naval Architecture, Ocean & Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;
    2. Shanghai Key Laboratory for Digital Maintenance of Buildings and Infrastructure, Shanghai 200240, China
  • Online:2022-08-31 Published:2022-08-15
  • Contact: DENG Xue-yuan (1973), associate professor, Ph.D. His main research interests cover architectural CAD collaborative design and integration, building collaborative platform based on BIM technology, etc
  • Supported by:
    “Thirteenth Five-Year” National Key R&D Plan (2016YFC0702001)

Abstract:

At present, the recognition technology of non-overlapped characters has been perfected, but it remains difficult to solve the recognition problem of common overlapped characters in scenarios such as the annotation of architectural engineering drawings, which hinders the breakthrough of automatic modeling technology based on 2D scanned drawings. To address the incapability of traditional character recognition methods to recognize overlapped characters, a new method was proposed for overlapped characters recognition in construction drawings based on adaptive scale edge features. Based on the spatial distribution characteristics of pixels, the overlapped character areas were preliminarily determined, and the adaptive scale edge features of characters were defined and extracted. The result combination of “position + content” was screened with the help of the bivariate matching probability function, and the global optimal principle was used instead of the absolute threshold as the identification standard. Finally, the correct recognition of overlapped characters was achieved. Different from the conventional idea of recognizing after repairing, the new method combined feature matching and interference filtering, character positioning and character recognition. The proposed method can solve the overlapping character recognition problem insolvable for mature commercial OCR such as Baidu, and the data experiment proves that this method is of high recognition accuracy.


Key words: overlapped characters, character recognition, adaptive scale, distribution probability, projection segmentation

CLC Number: