Practical Recognition System for Text Printed on Clear Reflected Material

Joint Authors

Agaian, Sos
Mohammad, Khader

Source

ISRN Machine Vision

Issue

Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-16, 16 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2012-10-14

Country of Publication

Egypt

No. of Pages

16

Main Subjects

Civil Engineering
Information Technology and Computer Science

Abstract EN

Text embedded in an image contains useful information for applications in the medical, industrial, commercial, and research fields.

While many systems have been designed to correctly identify text in images, no work addressing the recognition of degraded text on clear plastic has been found.

This paper posits novel methods and an apparatus for extracting text from an image with the practical assumption: (a) poor background contrast, (b) white, curved, and/or differing fonts or character width between sets of images, (c) dotted text printed on curved reflective material, and/or (d) touching characters.

Methods were evaluated using a total of 100 unique test images containing a variety of texts captured from water bottles.

These tests averaged a processing time of ~10 seconds (using MATLAB R2008A on an HP 8510 W with 4 G of RAM and 2.3 GHz of processor speed), and experimental results yielded an average recognition rate of 90 to 93% using customized systems generated by the proposed development.

American Psychological Association (APA)

Mohammad, Khader& Agaian, Sos. 2012. Practical Recognition System for Text Printed on Clear Reflected Material. ISRN Machine Vision،Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-457699

Modern Language Association (MLA)

Mohammad, Khader& Agaian, Sos. Practical Recognition System for Text Printed on Clear Reflected Material. ISRN Machine Vision No. 2012 (2012), pp.1-16.
https://search.emarefa.net/detail/BIM-457699

American Medical Association (AMA)

Mohammad, Khader& Agaian, Sos. Practical Recognition System for Text Printed on Clear Reflected Material. ISRN Machine Vision. 2012. Vol. 2012, no. 2012, pp.1-16.
https://search.emarefa.net/detail/BIM-457699

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-457699