A Bottom Up Procedure for Text Line Segmentation of Latin Script

In this paper we present a bottom up procedure for segmentation of text lines written or printed in the Latin script. The proposed method uses a combination of image morphology, feature extraction and Gaussian mixture model to perform this task. The experimental results show the validity of the procedure.Comment: Accepted and presented at the IEEE conference "International Conference on Advances in Computing, Communications and Informatics (ICACCI) 2017

Text Line Segmentation of Historical Documents: a Survey

There is a huge amount of historical documents in libraries and in various National Archives that have not been exploited electronically. Although automatic reading of complete pages remains, in most cases, a long-term objective, tasks such as word spotting, text/image alignment, authentication and extraction of specific fields are in use today. For all these tasks, a major step is document segmentation into text lines. Because of the low quality and the complexity of these documents (background noise, artifacts due to aging, interfering lines),automatic text line segmentation remains an open research field. The objective of this paper is to present a survey of existing methods, developed during the last decade, and dedicated to documents of historical interest.Comment: 25 pages, submitted version, To appear in International Journal on Document Analysis and Recognition, On line version available at http://www.springerlink.com/content/k2813176280456k3

Estimation of the Handwritten Text Skew Based on Binary Moments

Binary moments represent one of the methods for the text skew estimation in binary images. It has been used widely for the skew identification of the printed text. However, the handwritten text consists of text objects, which are characterized with different skews. Hence, the method should be adapted for the handwritten text. This is achieved with the image splitting into separate text objects made by the bounding boxes. Obtained text objects represent the isolated binary objects. The application of the moment-based method to each binary object evaluates their local text skews. Due to the accuracy, estimated skew data can be used as an input to the algorithms for the text line segmentation

HYBRID BINARIZTION TECHNIQUE FOR HISTORICAL MANUSCRIPTS

This paper presents a new hybrid approach for the binarization and enhancement of Historical Manuscript. This paper deals with degradations which occur due to shadows, non-uniform illumination, low contrast and strain. We follow two distinct method of Binarization with a pre-processing procedure using a adaptive Wiener filter, a rough estimation of foreground regions and a background surface calculation by interpolating neighboring background intensities. Further logical anding of the calculated background surface with compliment of second method result, performing final thresholding and post-processing in order to improve the quality of text regions. After extensive experiments, our method demonstrated superior performance against some wellknown techniques on numerous degraded document images as well as on Historical Manuscript in both manners qualitatively and quantitatively