A Laplacian Energy for Document Binarization

Author

Howe, Nicholas R.

Author_Institution

Dept. of Comput. Sci., Smith Coll., Northampton, MA, USA

fYear

2011

fDate

18-21 Sept. 2011

Firstpage

6

Lastpage

10

Abstract

This paper describes a new algorithm for document binarization, building upon recent work in energy-based segmentation methods. It uses the Laplacian operator to assess the local likelihood of foreground and background labels, Canny edge detection to identify likely discontinuities, and a graph cut implementation to efficiently find the minimum energy solution of an objective function combining these concepts. The results of this algorithm place it near the top on both the DIBCO-09 and H-DIBCO assessments.

Keywords

document image processing; edge detection; graph theory; mathematical operators; Canny edge detection; DIBCO-09; H-DIBCO; Laplacian energy; Laplacian operator; background label likelihood; discontinuity identification; document image binarization; energy-based segmentation method; foreground label likelihood; graph cut implementation; objective function; Image edge detection; Ink; Laplace equations; Markov processes; Text analysis; Training; Tuning; I.4.0.b Image processing software; I.4.6.b Graph-theoretic methods; I.4.6.d Pixel classification;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition (ICDAR), 2011 International Conference on

Conference_Location

Beijing

ISSN

1520-5363

Print_ISBN

978-1-4577-1350-7

Electronic_ISBN

1520-5363

Type

conf

DOI

10.1109/ICDAR.2011.11

Filename

6065266