Real World Uses of OCR for Modernization of Traffic system

Normally complete OCR methodology for recognizing documents, either printed or handwritten without any knowledge of the font, is presented.This methodology consists of three steps: The first two steps refer to creating a database for training using a set of documents, while the third one refers to recognition of new document images.First, a preprocessing step that includes image binarization and enhancement takes place.At a second step a top-down segmentation approach is used in order to detect text lines, words and characters.A clustering scheme is then adopted in order to group characters of similar shape.This is a semi-automatic procedure since the user is able to interact at any time in order to correct possible errors of clustering and assign an ASCII label.After this step, a database is created in order to be used for recognition.Finally, in the third step, for every new document image the above segmentation approach takes place while the recognition is based on the character database that has been produced at the previous step.

Publication Details

Journal
IJIREEICE
Published
2025-06-22
DOI
https://doi.org/10.17148/ijireeice.2025.13635
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
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article

Real World Uses of OCR for Modernization of Traffic system

IJIREEICE
Traffic Prediction and Management Techniques
article

Real World Uses of OCR for Modernization of Traffic system

article en

Abstract

Normally complete OCR methodology for recognizing documents, either printed or handwritten without any knowledge of the font, is presented.This methodology consists of three steps: The first two steps refer to creating a database for training using a set of documents, while the third one refers to recognition of new document images.First, a preprocessing step that includes image binarization and enhancement takes place.At a second step a top-down segmentation approach is used in order to detect text lines, words and characters.A clustering scheme is then adopted in order to group characters of similar shape.This is a semi-automatic procedure since the user is able to interact at any time in order to correct possible errors of clustering and assign an ASCII label.After this step, a database is created in order to be used for recognition.Finally, in the third step, for every new document image the above segmentation approach takes place while the recognition is based on the character database that has been produced at the previous step.

IJIREEICEVol. 13(6)
Sustainable cities and communities
Openalex Percentile: Top 85%
Traffic Prediction and Management Techniques
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Real World Uses of OCR for Modernization of Traffic system · IJIREEICE (2025) | TGRS Research Map | TGRS