OcrV1, PascalFrancis, Curation, bibRecord, 000633

Complex documents images segmentation based on steerable pyramid features

Identifieur interne : 000633 ( PascalFrancis/Curation ); précédent : 000632; suivant : 000634

Complex documents images segmentation based on steerable pyramid features

Auteurs : Mohamed Benjelil [France] ; Slim Kanoun [Tunisie] ; Rémy Mullot [France] ; Adel M. Alimi [Tunisie]

Source :

International journal on document analysis and recognition : (Print) [ 1433-2833 ] ; 2010.

RBID : Pascal:11-0227897

Descripteurs français

Pascal (Inist)
- Traitement document, Traitement image, Classification, Analyse documentaire, Reconnaissance caractère, Reconnaissance optique caractère, Système complexe, Texte, Caractère manuscrit, Représentation graphique, Image multiple, Banque image, Présentation document, Décomposition sous bande, Multilinguisme, Structure document, Document officiel, Extraction forme, Invariant, Analyse multirésolution, Segmentation image.
Wicri :
- topic : Classification, Multilinguisme, Document officiel.

English descriptors

KwdEn :
- Character recognition, Classification, Complex system, Document analysis, Document layout, Document processing, Document structure, Graphics, Image databank, Image processing, Image segmentation, Invariant, Manuscript character, Multilingualism, Multiple image, Multiresolution analysis, Official document, Optical character recognition, Pattern extraction, Subband decomposition, Text.

Abstract

Page segmentation and classification is very important in document layout analysis system before it is presented to an OCR system or for any other subsequent processing steps. In this paper, we propose an accurate and suitably designed system for complex documents segmentation. This system is based on steerable pyramid transform. The features extracted from pyramid sub-bands serve to locate and classify regions into text (either machine-printed or handwritten) and non-text (images, graphics, drawings or paintings) in some noise-infected, deformed, multilingual, multi-script document images. These documents contain tabular structures, logos, stamps, handwritten script blocks, photographs, etc. The encouraging and promising results obtained on 1,000 official complex document images data set are presented in this research paper. We compared our results with those from existing state-of-the-art methods. This comparison shows that the proposed method performs consistently well on large sets of complex document images.

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A11	`01`	`1`		`@1 BENJELIL (Mohamed)`
A11	`02`	`1`		`@1 KANOUN (Slim)`
A11	`03`	`1`		`@1 MULLOT (Rémy)`
A11	`04`	`1`		`@1 ALIMI (Adel M.)`
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C03	`06`	`X`	`ENG`	`@0 Optical character recognition @5 11`
C03	`06`	`X`	`SPA`	`@0 Reconocimento óptico de caracteres @5 11`
C03	`07`	`X`	`FRE`	`@0 Système complexe @5 12`
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C03	`09`	`X`	`ENG`	`@0 Manuscript character @5 14`
C03	`09`	`X`	`SPA`	`@0 Carácter manuscrito @5 14`
C03	`10`	`X`	`FRE`	`@0 Représentation graphique @5 15`
C03	`10`	`X`	`ENG`	`@0 Graphics @5 15`
C03	`10`	`X`	`SPA`	`@0 Grafo (curva) @5 15`
C03	`11`	`X`	`FRE`	`@0 Image multiple @5 16`
C03	`11`	`X`	`ENG`	`@0 Multiple image @5 16`
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C03	`13`	`X`	`SPA`	`@0 Presentación documento @5 18`
C03	`14`	`X`	`FRE`	`@0 Décomposition sous bande @5 19`
C03	`14`	`X`	`ENG`	`@0 Subband decomposition @5 19`
C03	`14`	`X`	`SPA`	`@0 Descomposición subbanda @5 19`
C03	`15`	`X`	`FRE`	`@0 Multilinguisme @5 20`
C03	`15`	`X`	`ENG`	`@0 Multilingualism @5 20`
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C03	`16`	`X`	`FRE`	`@0 Structure document @5 21`
C03	`16`	`X`	`ENG`	`@0 Document structure @5 21`
C03	`16`	`X`	`SPA`	`@0 Estructura documental @5 21`
C03	`17`	`X`	`FRE`	`@0 Document officiel @5 22`
C03	`17`	`X`	`ENG`	`@0 Official document @5 22`
C03	`17`	`X`	`SPA`	`@0 Documento oficial @5 22`
C03	`18`	`X`	`FRE`	`@0 Extraction forme @5 23`
C03	`18`	`X`	`ENG`	`@0 Pattern extraction @5 23`
C03	`18`	`X`	`SPA`	`@0 Extracción forma @5 23`
C03	`19`	`X`	`FRE`	`@0 Invariant @5 24`
C03	`19`	`X`	`ENG`	`@0 Invariant @5 24`
C03	`19`	`X`	`SPA`	`@0 Invariante @5 24`
C03	`20`	`X`	`FRE`	`@0 Analyse multirésolution @5 41`
C03	`20`	`X`	`ENG`	`@0 Multiresolution analysis @5 41`
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C03	`21`	`X`	`FRE`	`@0 Segmentation image @4 CD @5 96`
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Le document en format XML

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<fC01 i1="01" l="ENG"><s0>Page segmentation and classification is very important in document layout analysis system before it is presented to an OCR system or for any other subsequent processing steps. In this paper, we propose an accurate and suitably designed system for complex documents segmentation. This system is based on steerable pyramid transform. The features extracted from pyramid sub-bands serve to locate and classify regions into text (either machine-printed or handwritten) and non-text (images, graphics, drawings or paintings) in some noise-infected, deformed, multilingual, multi-script document images. These documents contain tabular structures, logos, stamps, handwritten script blocks, photographs, etc. The encouraging and promising results obtained on 1,000 official complex document images data set are presented in this research paper. We compared our results with those from existing state-of-the-art methods. This comparison shows that the proposed method performs consistently well on large sets of complex document images.</s0>
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<s5>13</s5>
</fC03>
<fC03 i1="08" i2="X" l="SPA"><s0>Texto</s0>
<s5>13</s5>
</fC03>
<fC03 i1="09" i2="X" l="FRE"><s0>Caractère manuscrit</s0>
<s5>14</s5>
</fC03>
<fC03 i1="09" i2="X" l="ENG"><s0>Manuscript character</s0>
<s5>14</s5>
</fC03>
<fC03 i1="09" i2="X" l="SPA"><s0>Carácter manuscrito</s0>
<s5>14</s5>
</fC03>
<fC03 i1="10" i2="X" l="FRE"><s0>Représentation graphique</s0>
<s5>15</s5>
</fC03>
<fC03 i1="10" i2="X" l="ENG"><s0>Graphics</s0>
<s5>15</s5>
</fC03>
<fC03 i1="10" i2="X" l="SPA"><s0>Grafo (curva)</s0>
<s5>15</s5>
</fC03>
<fC03 i1="11" i2="X" l="FRE"><s0>Image multiple</s0>
<s5>16</s5>
</fC03>
<fC03 i1="11" i2="X" l="ENG"><s0>Multiple image</s0>
<s5>16</s5>
</fC03>
<fC03 i1="11" i2="X" l="SPA"><s0>Imagen múltiple</s0>
<s5>16</s5>
</fC03>
<fC03 i1="12" i2="X" l="FRE"><s0>Banque image</s0>
<s5>17</s5>
</fC03>
<fC03 i1="12" i2="X" l="ENG"><s0>Image databank</s0>
<s5>17</s5>
</fC03>
<fC03 i1="12" i2="X" l="SPA"><s0>Banco imagen</s0>
<s5>17</s5>
</fC03>
<fC03 i1="13" i2="X" l="FRE"><s0>Présentation document</s0>
<s5>18</s5>
</fC03>
<fC03 i1="13" i2="X" l="ENG"><s0>Document layout</s0>
<s5>18</s5>
</fC03>
<fC03 i1="13" i2="X" l="SPA"><s0>Presentación documento</s0>
<s5>18</s5>
</fC03>
<fC03 i1="14" i2="X" l="FRE"><s0>Décomposition sous bande</s0>
<s5>19</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Subband decomposition</s0>
<s5>19</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Descomposición subbanda</s0>
<s5>19</s5>
</fC03>
<fC03 i1="15" i2="X" l="FRE"><s0>Multilinguisme</s0>
<s5>20</s5>
</fC03>
<fC03 i1="15" i2="X" l="ENG"><s0>Multilingualism</s0>
<s5>20</s5>
</fC03>
<fC03 i1="15" i2="X" l="SPA"><s0>Multilingüismo</s0>
<s5>20</s5>
</fC03>
<fC03 i1="16" i2="X" l="FRE"><s0>Structure document</s0>
<s5>21</s5>
</fC03>
<fC03 i1="16" i2="X" l="ENG"><s0>Document structure</s0>
<s5>21</s5>
</fC03>
<fC03 i1="16" i2="X" l="SPA"><s0>Estructura documental</s0>
<s5>21</s5>
</fC03>
<fC03 i1="17" i2="X" l="FRE"><s0>Document officiel</s0>
<s5>22</s5>
</fC03>
<fC03 i1="17" i2="X" l="ENG"><s0>Official document</s0>
<s5>22</s5>
</fC03>
<fC03 i1="17" i2="X" l="SPA"><s0>Documento oficial</s0>
<s5>22</s5>
</fC03>
<fC03 i1="18" i2="X" l="FRE"><s0>Extraction forme</s0>
<s5>23</s5>
</fC03>
<fC03 i1="18" i2="X" l="ENG"><s0>Pattern extraction</s0>
<s5>23</s5>
</fC03>
<fC03 i1="18" i2="X" l="SPA"><s0>Extracción forma</s0>
<s5>23</s5>
</fC03>
<fC03 i1="19" i2="X" l="FRE"><s0>Invariant</s0>
<s5>24</s5>
</fC03>
<fC03 i1="19" i2="X" l="ENG"><s0>Invariant</s0>
<s5>24</s5>
</fC03>
<fC03 i1="19" i2="X" l="SPA"><s0>Invariante</s0>
<s5>24</s5>
</fC03>
<fC03 i1="20" i2="X" l="FRE"><s0>Analyse multirésolution</s0>
<s5>41</s5>
</fC03>
<fC03 i1="20" i2="X" l="ENG"><s0>Multiresolution analysis</s0>
<s5>41</s5>
</fC03>
<fC03 i1="20" i2="X" l="SPA"><s0>Análisis multiresolución</s0>
<s5>41</s5>
</fC03>
<fC03 i1="21" i2="X" l="FRE"><s0>Segmentation image</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="21" i2="X" l="ENG"><s0>Image segmentation</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="21" i2="X" l="SPA"><s0>Segmentación de imágenes</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fN21><s1>150</s1>
</fN21>
<fN44 i1="01"><s1>OTO</s1>
</fN44>
<fN82><s1>OTO</s1>
</fN82>
</pA>
</standard>
</inist>
</record>

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   |texte=   Complex documents images segmentation based on steerable pyramid features
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Complex documents images segmentation based on steerable pyramid features

Complex documents images segmentation based on steerable pyramid features

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Abstract

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