An Analysis of Adaptive Approach for Document Binarization

Abstract

Abstract Binarization is an initial step in document image analysis for differentiate text area from background. Determination of binarization technique is really important to retrieve all the text information especially from degraded document image. This paper explains about adaptive binarization using Gatos’s method. Gatos’s method is doing preprocessing, foreground estimation using Sauvola’s method, background estimation, upsampling, final thresholding and postprocessing. In this paper, Sauvola’s method is final thresholding from Wiener filter image result and source image, and count F-Measure from both of these binary image results. By using optimum constant value on k value, n local window, K sw and K sw1, Gatos’s method can produced binary image better than Sauvola’s method based on F-Measure value. Sauvola’s method produces average value F=84,62%, Sauvola’s method with Wiener filter produces average value F=99.06% and Gatos’s method produces average value F=99,43%. Keyword : Degraded Document Image, Adaptive Approcah for Binarization, Gatos’s  Method, Sauvola’s Method DOI: 10.18495/comengapp.22.185194