OCR based on mathematical morphology

Junior Barrera; Routo Terada; Roberto Alencar Lotufo; Nina Sumiko Tomita Hirata; Roberto Hirata Jr.; F. A. Zampirolli

doi:10.1117/12.304600

6 April 1998 OCR based on mathematical morphology

Junior Barrera, Routo Terada, Roberto Alencar Lotufo, Nina Sumiko Tomita Hirata, Roberto Hirata Jr., F. A. Zampirolli

Author Affiliations +

Proceedings Volume 3304, Nonlinear Image Processing IX; (1998) https://doi.org/10.1117/12.304600
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

We present the prototype of an OCR that was designed and implemented at the Institute of Mathematics and Statistics of the University of Sao Paulo. The remarkable characteristic of this system is that all the necessary image processing tasks are performed by Mathematical Morphology operators (the so called morphological operators). Thus, we have developed morphological operators to segment scanned images (i.e., identify objects as characters, words and paragraphs), and recognize font styles and character semantics. The morphological operators that perform segmentation were designed by classical heuristic techniques, while the ones that recognize fonts and characters were designed automatically by new computational learning techniques. The fundamental idea under these techniques is the estimation of a morphological operator from observations of input-output image pairs, that describe its ideal performance. The morphological operators designed have been integrated in a system that translate scanned images into RTF text files, with reasonable correction and time performance. This system has been developed in the KHOROS platform, using the MMach (for morphological operators design heuristically) and PAC (for morphological operators designed by learning) toolboxes.

Citation Download Citation

Junior Barrera, Routo Terada, Roberto Alencar Lotufo, Nina Sumiko Tomita Hirata, Roberto Hirata Jr., and F. A. Zampirolli "OCR based on mathematical morphology", Proc. SPIE 3304, Nonlinear Image Processing IX, (6 April 1998); https://doi.org/10.1117/12.304600

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