Authors:
Neucimar Jerônimo Leite
and
Leyza Baldo Dorini
Affiliation:
University of Campinas - UNICAMP, Brazil
Keyword(s):
Scale-space, Document binarization, Image analysis.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Image Formation and Preprocessing
;
Mathematical Morphology
;
Segmentation and Grouping
Abstract:
Basically, document image binarization consists on the segmentation of scanned gray level images into text and background, and is a basic preprocessing stage in many image analysis systems. It is essential to threshold the document image reliably in order to extract useful information and make further processing such as character recognition and feature extraction. The main difficulties arise when dealing with poor quality document images, containing nonuniform illumination, shadows and smudge, for example. This paper presents an efficient morphological-based document image binarization technique that is able to cope with these problems. We evaluate the proposed approach for different classes of images, such as historical and machine-printed documents, obtaining promising results.