OcrV1, PascalFrancis, Curation, bibRecord, 000482

Script identification from Indian documents

Identifieur interne : 000482 ( PascalFrancis/Curation ); précédent : 000481; suivant : 000483

Script identification from Indian documents

Auteurs : GOPAL DATT JOSHI [Inde] ; Saurabh Garg [Inde] ; Jayanthi Sivaswamy [Inde]

Source :

Lecture notes in computer science [ 0302-9743 ] ; 2006.

RBID : Pascal:08-0029049

Descripteurs français

Pascal (Inist)
- Reconnaissance forme, Analyse documentaire, Structure document, Reconnaissance caractère, Reconnaissance optique caractère, Texte, Traitement document, Segmentation image, Traitement image, Traitement donnée, Base donnée très grande, Multilinguisme, Archive, Plan classement, Classification hiérarchique, Filtre multicanal, Extraction forme, Filtre Gabor, Optimisation, Conception optimale, Méthode échelle multiple.
Wicri :
- topic : Multilinguisme.

English descriptors

KwdEn :
- Archive, Character recognition, Classification scheme, Data processing, Document analysis, Document processing, Document structure, Gabor filter, Hierarchical classification, Image processing, Image segmentation, Multichannel filter, Multilingualism, Multiscale method, Optical character recognition, Optimal design, Optimization, Pattern extraction, Pattern recognition, Text, Very large databases.

Abstract

Automatic identification of a script in a given document image facilitates many important applications such as automatic archiving of multilingual documents, searching online archives of document images and for the selection of script specific OCR in a multilingual environment. In this paper, we present a scheme to identify different Indian scripts from a document image. This scheme employs hierarchical classification which uses features consistent with human perception. Such features are extracted from the responses of a multi-channel log-Gabor filter bank, designed at an optimal scale and multiple orientations. In the first stage, the classifier groups the scripts into five major classes using global features. At the next stage, a sub-classification is performed based on script-specific features. All features are extracted globally from a given text block which does not require any complex and reliable segmentation of the document image into lines and characters. Thus the proposed scheme is efficient and can be used for many practical applications which require processing large volumes of data. The scheme has been tested on 10 Indian scripts and found to be robust to skew generated in the process of scanning and relatively insensitive to change in font size. This proposed system achieves an overall classification accuracy of 97.11% on a large testing data set. These results serve to establish the utility of global approach to classification of scripts.

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Le document en format XML

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<fC03 i1="10" i2="X" l="ENG"><s0>Data processing</s0>
<s5>12</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Tratamiento datos</s0>
<s5>12</s5>
</fC03>
<fC03 i1="11" i2="3" l="FRE"><s0>Base donnée très grande</s0>
<s5>13</s5>
</fC03>
<fC03 i1="11" i2="3" l="ENG"><s0>Very large databases</s0>
<s5>13</s5>
</fC03>
<fC03 i1="12" i2="X" l="FRE"><s0>Multilinguisme</s0>
<s5>18</s5>
</fC03>
<fC03 i1="12" i2="X" l="ENG"><s0>Multilingualism</s0>
<s5>18</s5>
</fC03>
<fC03 i1="12" i2="X" l="SPA"><s0>Multilingüismo</s0>
<s5>18</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Archive</s0>
<s5>19</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Archive</s0>
<s5>19</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Archivo</s0>
<s5>19</s5>
</fC03>
<fC03 i1="14" i2="X" l="FRE"><s0>Plan classement</s0>
<s5>20</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Classification scheme</s0>
<s5>20</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Plan clasificación</s0>
<s5>20</s5>
</fC03>
<fC03 i1="15" i2="X" l="FRE"><s0>Classification hiérarchique</s0>
<s5>21</s5>
</fC03>
<fC03 i1="15" i2="X" l="ENG"><s0>Hierarchical classification</s0>
<s5>21</s5>
</fC03>
<fC03 i1="15" i2="X" l="SPA"><s0>Clasificación jerarquizada</s0>
<s5>21</s5>
</fC03>
<fC03 i1="16" i2="X" l="FRE"><s0>Filtre multicanal</s0>
<s5>22</s5>
</fC03>
<fC03 i1="16" i2="X" l="ENG"><s0>Multichannel filter</s0>
<s5>22</s5>
</fC03>
<fC03 i1="16" i2="X" l="SPA"><s0>Filtro multicanal</s0>
<s5>22</s5>
</fC03>
<fC03 i1="17" i2="X" l="FRE"><s0>Extraction forme</s0>
<s5>23</s5>
</fC03>
<fC03 i1="17" i2="X" l="ENG"><s0>Pattern extraction</s0>
<s5>23</s5>
</fC03>
<fC03 i1="17" i2="X" l="SPA"><s0>Extracción forma</s0>
<s5>23</s5>
</fC03>
<fC03 i1="18" i2="X" l="FRE"><s0>Filtre Gabor</s0>
<s5>24</s5>
</fC03>
<fC03 i1="18" i2="X" l="ENG"><s0>Gabor filter</s0>
<s5>24</s5>
</fC03>
<fC03 i1="18" i2="X" l="SPA"><s0>Filtro Gabor</s0>
<s5>24</s5>
</fC03>
<fC03 i1="19" i2="X" l="FRE"><s0>Optimisation</s0>
<s5>25</s5>
</fC03>
<fC03 i1="19" i2="X" l="ENG"><s0>Optimization</s0>
<s5>25</s5>
</fC03>
<fC03 i1="19" i2="X" l="SPA"><s0>Optimización</s0>
<s5>25</s5>
</fC03>
<fC03 i1="20" i2="X" l="FRE"><s0>Conception optimale</s0>
<s5>26</s5>
</fC03>
<fC03 i1="20" i2="X" l="ENG"><s0>Optimal design</s0>
<s5>26</s5>
</fC03>
<fC03 i1="20" i2="X" l="SPA"><s0>Concepción optimal</s0>
<s5>26</s5>
</fC03>
<fC03 i1="21" i2="X" l="FRE"><s0>Méthode échelle multiple</s0>
<s5>27</s5>
</fC03>
<fC03 i1="21" i2="X" l="ENG"><s0>Multiscale method</s0>
<s5>27</s5>
</fC03>
<fC03 i1="21" i2="X" l="SPA"><s0>Método escala múltiple</s0>
<s5>27</s5>
</fC03>
<fN21><s1>052</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
<pR><fA30 i1="01" i2="1" l="ENG"><s1>DAS 2006</s1>
<s2>7</s2>
<s3>Nelson NZL</s3>
<s4>2006</s4>
</fA30>
</pR>
</standard>
</inist>
</record>

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   |texte=   Script identification from Indian documents
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Script identification from Indian documents

Script identification from Indian documents

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