Italic detection and rectification
Identifieur interne : 000F33 ( Main/Exploration ); précédent : 000F32; suivant : 000F34Italic detection and rectification
Auteurs : Kuo-Chin Fan [Taïwan] ; Chien-Hsiang Huang [Taïwan]Source :
- Journal of information science and engineering [ 1016-2364 ] ; 2007.
Descripteurs français
- Pascal (Inist)
- Wicri :
- topic : Classification.
English descriptors
- KwdEn :
Abstract
In this paper, a novel italic detection and rectification method without the prerequisite of character recognition is proposed. An italic style character can be obtained by performing shear transformation on its corresponding non-italic style character. Traditional italic detection methods have to be operated at least on the word, sentence or even the whole paragraph. The merit of the proposed method is that it can be operated directly on a single character so that more accurate statistical information can be obtained. The rationale of our proposed method is that the difference of certain features derived from italic style characters after shear transformation will be canceled, whereas the difference will be more obvious for non-italic style (normal style) characters. In our proposed approach, the virtual strokes embedded in the considered character image are extracted first. Then, reverse transformation is operated on the considered character image. The 26 upper and 26 lower alphabets are classified into three classes based on the structural information of the extracted virtual strokes. The italic and non-italic style characters can then be distinguished based on the classification rule devised for each class of characters. Last, the exact shear angle of the identified italic character is calculated to perform more accurate reverse shear transformation to rectify the italic style character into normal (non-italic) style character to facilitate the later OCR task. Experiments were conducted on 50 document images with mixed italic and normal style characters. Satisfactory accuracy rate 99.59% for italic style characters and 99.85% for normal style characters are achieved. Experimental results verify the validity of our proposed method in distinguishing italic and non-italic style characters.
Affiliations:
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Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en" level="a">Italic detection and rectification</title><author><name sortKey="Fan, Kuo Chin" sort="Fan, Kuo Chin" uniqKey="Fan K" first="Kuo-Chin" last="Fan">Kuo-Chin Fan</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Institute of Computer Science and Information Engineering National Central University</s1><s2>Chungli, 320</s2><s3>TWN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ></inist:fA14><country>Taïwan</country><wicri:noRegion>Institute of Computer Science and Information Engineering National Central University</wicri:noRegion></affiliation></author><author><name sortKey="Huang, Chien Hsiang" sort="Huang, Chien Hsiang" uniqKey="Huang C" first="Chien-Hsiang" last="Huang">Chien-Hsiang Huang</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Institute of Computer Science and Information Engineering National Central University</s1><s2>Chungli, 320</s2><s3>TWN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ></inist:fA14><country>Taïwan</country><wicri:noRegion>Institute of Computer Science and Information Engineering National Central University</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">07-0170808</idno><date when="2007">2007</date><idno type="stanalyst">PASCAL 07-0170808 INIST</idno><idno type="RBID">Pascal:07-0170808</idno><idno type="wicri:Area/PascalFrancis/Corpus">000351</idno><idno type="wicri:Area/PascalFrancis/Curation">000435</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">000275</idno><idno type="wicri:doubleKey">1016-2364:2007:Fan K:italic:detection:and</idno><idno type="wicri:Area/Main/Merge">000F46</idno><idno type="wicri:Area/Main/Curation">000F33</idno><idno type="wicri:Area/Main/Exploration">000F33</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Italic detection and rectification</title><author><name sortKey="Fan, Kuo Chin" sort="Fan, Kuo Chin" uniqKey="Fan K" first="Kuo-Chin" last="Fan">Kuo-Chin Fan</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Institute of Computer Science and Information Engineering National Central University</s1><s2>Chungli, 320</s2><s3>TWN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ></inist:fA14><country>Taïwan</country><wicri:noRegion>Institute of Computer Science and Information Engineering National Central University</wicri:noRegion></affiliation></author><author><name sortKey="Huang, Chien Hsiang" sort="Huang, Chien Hsiang" uniqKey="Huang C" first="Chien-Hsiang" last="Huang">Chien-Hsiang Huang</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>Institute of Computer Science and Information Engineering National Central University</s1><s2>Chungli, 320</s2><s3>TWN</s3><sZ>1 aut.</sZ><sZ>2 aut.</sZ></inist:fA14><country>Taïwan</country><wicri:noRegion>Institute of Computer Science and Information Engineering National Central University</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">Journal of information science and engineering</title><title level="j" type="abbreviated">J. inf. sci. eng.</title><idno type="ISSN">1016-2364</idno><imprint><date when="2007">2007</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Journal of information science and engineering</title><title level="j" type="abbreviated">J. inf. sci. eng.</title><idno type="ISSN">1016-2364</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Character recognition</term><term>Classification</term><term>Expert system</term><term>Image processing</term><term>Knowledge base</term><term>Optical character recognition</term><term>Pattern recognition</term><term>Probabilistic approach</term><term>Rectification</term><term>Sentence</term><term>Shear</term><term>Statistical analysis</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Reconnaissance caractère</term><term>Reconnaissance forme</term><term>Traitement image</term><term>Système expert</term><term>Classification</term><term>Reconnaissance optique caractère</term><term>Rectification</term><term>Cisaillement</term><term>Phrase</term><term>Analyse statistique</term><term>Approche probabiliste</term><term>Base connaissance</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Classification</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In this paper, a novel italic detection and rectification method without the prerequisite of character recognition is proposed. An italic style character can be obtained by performing shear transformation on its corresponding non-italic style character. Traditional italic detection methods have to be operated at least on the word, sentence or even the whole paragraph. The merit of the proposed method is that it can be operated directly on a single character so that more accurate statistical information can be obtained. The rationale of our proposed method is that the difference of certain features derived from italic style characters after shear transformation will be canceled, whereas the difference will be more obvious for non-italic style (normal style) characters. In our proposed approach, the virtual strokes embedded in the considered character image are extracted first. Then, reverse transformation is operated on the considered character image. The 26 upper and 26 lower alphabets are classified into three classes based on the structural information of the extracted virtual strokes. The italic and non-italic style characters can then be distinguished based on the classification rule devised for each class of characters. Last, the exact shear angle of the identified italic character is calculated to perform more accurate reverse shear transformation to rectify the italic style character into normal (non-italic) style character to facilitate the later OCR task. Experiments were conducted on 50 document images with mixed italic and normal style characters. Satisfactory accuracy rate 99.59% for italic style characters and 99.85% for normal style characters are achieved. Experimental results verify the validity of our proposed method in distinguishing italic and non-italic style characters.</div></front></TEI><affiliations><list><country><li>Taïwan</li></country></list><tree><country name="Taïwan"><noRegion><name sortKey="Fan, Kuo Chin" sort="Fan, Kuo Chin" uniqKey="Fan K" first="Kuo-Chin" last="Fan">Kuo-Chin Fan</name></noRegion><name sortKey="Huang, Chien Hsiang" sort="Huang, Chien Hsiang" uniqKey="Huang C" first="Chien-Hsiang" last="Huang">Chien-Hsiang Huang</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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