Detection and segmentation of lines and words in Gurmukhi handwritten text

Abstract

The scanned text image is a non editable image though it has the text but one can not edit it or make any change, if required, to that scanned document. This provides a basis for the optical character recognition (OCR) theory. OCR is the process of recognizing a segmented part of the scanned image as a character. The overall OCR process consists of three major sub processes like pre processing, segmentation and then recognition. Out of these three, the segmentation process is the back bone of the overall OCR process. We can say that the segmentation process is the most significant process because if the segmentation is incorrect then we can not have the correct results; it is just like garbage in and garbage out. But it is not an easy job, because segmentation is one of the complex processes. It is more difficult if the document is handwritten because in that case only few points are there which can be used to make segmentation. In this paper, we formulate an approach to segment the scanned document image. As per this approach, initially this considers the whole image as one large window. Then this large window is broken into less large windows giving lines, once the lines are identified then each window consisting of a line is used to find a word present in that line and finally to characters. For that purpose we used the concept of variable sized window, that is, the window whose size can be adjusted according to needs. This concept was implemented and results were analyzed. After the analysis the same concept was modified and finally tried on different documents and we got good reasonable results.

Offline Handwritten Gurmukhi Character Recognition: A Review

“…A novel method is offered for recognition & segmentation of touching characters. [3] 2008 Elastic matching In this the author has projected two stages for the recognition. In the first phase unidentified strokes are recognized and in the second stage the author has evaluated the characters with the help of strokes that are found in the first stage [5].…”

“…To find the K-nearest neighbors, the authors calculated the Euclidian distance b/w test point and reference point. Rajiv Kumar et al [3] showed how segmentation can be done in character recognition of Gurmukhi script. In this work the authors gave emphasis on the segmentation of words and lines in Handwritten Gurmukhi text.R.K Sharma et al [4] have reported that by using various features like diagonal, directional & zoning & K-NN, Bayesian classifiers we can compare the handwriting of writers.Vipin Narang projected a approach based on parts or technique suitable for scene images.…”

A Novel Approach for Word Segmentation in Correlation based OCR System

“…An improvement of 3% in recognition rate from 94.35% to 97.34% has been reported on clean images using the post-processing techniques. Rajiv Kumar and Amardeep Singh (2010) [6] described that segmentation process is the back bone of the overall OCR process. They said that the segmentation process is the most significant process because if the segmentation is incorrect then they cannot have the correct results; it is just like garbage in and garbage out.…”

“…This forms the bases of OCR theory. [6] OCR system model is mainly divided into three sub processes.1) Preprocessing of scanned image. 2) Segmentation text of preprocessed image.…”

Morphological Operations and Projection Profiles based Segmentation of Handwritten Kannada Document

“…An approach to segment the scanned document image is presented in [17]. Here the whole image is considered as one large window.…”