Paper
25 April 2008 Invariant approach to the character classification
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Abstract
Image moments analysis is a very useful tool which allows image description invariant to translation and rotation, scale change and some types of image distortions. The aim of this work was development of simple method for fast and reliable classification of characters by using Hu's and affine moment invariants. Measure of Eucleidean distance was used as a discrimination feature with statistical parameters estimated. The method was tested in classification of Times New Roman font letters as well as sets of the handwritten characters. It is shown that using all Hu's and three affine invariants as discrimination set improves recognition rate by 30%.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kristina Šariri and Nazif Demoli "Invariant approach to the character classification", Proc. SPIE 7000, Optical and Digital Image Processing, 70001J (25 April 2008); https://doi.org/10.1117/12.781261
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Cited by 1 scholarly publication.
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KEYWORDS
Image analysis

Distance measurement

Optical character recognition

Statistical analysis

Digital image processing

Image classification

Prototyping

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