Title :
A Laplacian Energy for Document Binarization
Author :
Howe, Nicholas R.
Author_Institution :
Dept. of Comput. Sci., Smith Coll., Northampton, MA, USA
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;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2011.11
