Line and Word Segmentation of handwritten text documents written in Gurmukhi Script using mid point detection technique

Jindal, Payal; Jindal, Balkrishan

doi:10.1109/raecs.2015.7453388

Cited by 14 publications

(5 citation statements)

References 4 publications

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“…Arti cial Intelligence (AI) is bridging the gap between the capabilities of humans and computers. One such area is Computer Vision [1]. e primary aim of this eld is to make the computers behave as humans, perceive it in the same manner, and also use the knowledge for various tasks like for image recognition, image analysis, image classi cation, natural language processing (NLP), and so on.…”

Section: Introductionmentioning

confidence: 99%

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[Retracted] Optimized CNN‐Based Recognition of District Names of Punjab State in Gurmukhi Script

Sharma

Gupta

et al. 2022

Journal of Mathematics

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Automation of Postal systems has the major research scope in the field of automation. To create Postal Automation set-up for countries like India is a tedious task if compared with other countries because of India’s multiscript and multilingual behavior. This work will help in recognizing the “Gurmukhi” handwritten district names of the State Punjab. To recognize the district names, a CNN-based architecture is proposed by employing a Holistic approach. For this, an image database of 22000 samples is prepared having 1000 sample images for every district name which is collected from 500 different writers. Maximum accuracy on validation data achieved by the proposed Model is 99%.

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Section: Introductionmentioning

confidence: 99%

“…Similarly, Recognition of text can be done using Deep Learning which is the subset of AI. In this, automatic feature extraction and classi cation is done [1]. District names recognition helps in the automation of the postal system.…”

Section: Introductionmentioning

confidence: 99%

[Retracted] Optimized CNN‐Based Recognition of District Names of Punjab State in Gurmukhi Script

Sharma

Gupta

et al. 2022

Journal of Mathematics

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“…Software validation will give the accuracy of the particular system in verifying signatures. Orientation of the signature is interpreted and if the user signs in wrong orientation, then that mean the signature is forgery signature [ 15 ]. Also, pressure while signing would be checked, if shown different pressure while signing a signature that also causes it to be verified as a forgery.…”

Section: Matchingmentioning

confidence: 99%

A Review of Robust Automated Handwriting Recognition System

Bhargav,

Parmar

2024

IJSREM

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Handwriting is often used to identify personality characteristics that are expressed by neural patterns in the brain. During the prosecution of any crime, the authenticity of a person's handwriting is often subjected to forensic handwriting analysis in order toascertain authorship. Automated handwriting analysis is fast, precise, and better than visual inspection at identifying handwriting. It is also effective and free of human errors. One of the most effective forensic science processes is the use of an automated handwriting recognition system. It focuses on determining a person's characteristics or attributesof computer vision and image recognition. To boost precision, the new approach focuses on automated handwriting analysis systems. It is essential to use handwriting recognition software, and it must be developed to understand more languages. This paper reviews some of the most efficient automated handwriting identification systems and emphasizes the importance of such systems in handwriting analysis processes. Keywords: Automated Handwriting Recognition System, Image Processing, Acquisition, Pre-Processing, Feature Extraction, Matching

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“…Vishwas H. S et al [35] proposed smearing techniques for Kannada document. In [36] authors proposed midpoint detection approach for Gurmukhi handwritten documents. In [37] Dr.S.Pannirselvam et al proposed projection method for Tamil handwritten documents.…”

Section: Related Workmentioning

confidence: 99%

A novel method for segmenting and straightening of text lines in handwritten Telugu documents based on smearing and regression approach

Subrahmanyam

Kumar²,

Reddy³

2018

IJET

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In handwritten document images, segmenting text lines is a very challenging task due to various reasons like variability in intra baseline skew and inter line distance between text lines. So far, no work is reported in the literature for the straightening of handwritten Telugu languages. Telugu is one of the most popular languages of India that is spoken by more than 80 million people especially in South India. Telugu characters are mostly compound characters and that is way the straightening task of Telugu document is more challenging tasks than European languages. This paper introduces a novel approach for segmenting and straightening text lines of handwritten Telugu documents based on smearing and regression approach (SRA). This method initially performs preprocessing and estimates parameters by dividing into connected components of Telugu script. A horizontal and vertical run length-smearing algorithm is used in this paper to shape text lines. To identify text lines more precisely cubic polynomial regression is used between vertical midpoints of two blocks of compound handwritten Telugu characters. A simple logic is derived on this to achieve final process. We tested the proposed algorithm with three different kind of 1000 handwritten documents. The performance of proposed method is evaluated by using matchScore, detection rate, recognition accuracy and F-measure. The experimental results indicates the efficiency of the proposed method over the existing methods.

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Line and Word Segmentation of handwritten text documents written in Gurmukhi Script using mid point detection technique

Cited by 14 publications

References 4 publications

[Retracted] Optimized CNN‐Based Recognition of District Names of Punjab State in Gurmukhi Script

[Retracted] Optimized CNN‐Based Recognition of District Names of Punjab State in Gurmukhi Script

A Review of Robust Automated Handwriting Recognition System

A novel method for segmenting and straightening of text lines in handwritten Telugu documents based on smearing and regression approach

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