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High-order statistical texture analysis -: font recognition applied
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DOI：10.1016/j.patrec.2004.09.038.png)
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A new optical font recognition technique is proposed in this work. The new approach is based on global texture analysis, where statistical methods are used to identify and classify font features. The font recognition is performed by taking the document as a simple image, where one or several types of fonts are present. The identification is not performed letter by letter as with conventional approaches. In the proposed method a window analysis is employed to obtain the features of the document, using fourth and third order moments. The new technique does not involve a study of local typography; therefore, it is content independent. A detailed study was performed with 8 types of fonts commonly used in the Spanish language. Each type of font can have four styles that lead, to 32 font combinations. The font recognition with clean images is 100% accurate. Also, the new method was tested by adding Gaussian noise to clean images, so as to study the impact of image degradation on font recognition. The robustness of the algorithm is also examined in terms of varying resolution. (C) 2004 Elsevier B.V. All rights reserved.
Keyword:
texture analysis
optical font recognition (OFR)
optical character recognition (OCR) and high order statistics (HOS)
期刊
IF:
3.3
论文数:
8.0K
被引数:
1.6W
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