Unconstrained Handwritten Text Line Segmentation: An Improved Technique

Y.C. Kiran*, Mohammadi**, V.N. Manjunath Aradhya***
* Department of Computer science, Jain University, Bengaluru, India.
** Behsan Mellat, Iran
*** Department of MCA, Sri Jayachamarajendra College of Engineering, Mysuru, India.
Periodicity:October - December'2014
DOI : https://doi.org/10.26634/jip.1.4.3035

Abstract

Handwritten text line segmentation is still a challenging area in document image analysis. This is due to the variation of handwritten style from individual to individual causing many problems like multi-skewed, overlapping and touching text lines. In this paper, authors have proposed an improved technique for handwritten text line segmentation to the method proposed in [1]. The proposed method consists of four major phases, which includes piece-wise painting algorithm, skew estimation, line drawing and edge detection process. The proposed method is implemented on dataset of Kannada, English and comprising of Persian, Oriya and Bangla documents. The success rate of the technique, as observed experimentally was satisfactory and it may contribute significantly for the development of applications related to handwritten OCR (Optical Character Recognition).

Keywords

Document Image Analysis, Handwritten Text Line Segmentation, OCR, Edge Detection, Handwritten Character Recognition

How to Cite this Article?

Kiran, Y.C., Mohammadi, and Aradhya, V.N. (2014). Unconstrained Handwritten Text Line Segmentation: An Improved Technique. i-manager’s Journal on Image Processing, 1(4), 8-16. https://doi.org/10.26634/jip.1.4.3035

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