Presentation is loading. Please wait.

Presentation is loading. Please wait.

FRE 2645 ICISP’2003 : Agadir, Morocco : 24 June, 2003 Symbol Recognition by Global Local Structural Approaches, Based on Scenario Use, and with a XML Representation.

Published byVanessa Holt Modified over 8 years ago

Similar presentations

Presentation on theme: "FRE 2645 ICISP’2003 : Agadir, Morocco : 24 June, 2003 Symbol Recognition by Global Local Structural Approaches, Based on Scenario Use, and with a XML Representation."— Presentation transcript:

1 FRE 2645 ICISP’2003 : Agadir, Morocco : 24 June, 2003 Symbol Recognition by Global Local Structural Approaches, Based on Scenario Use, and with a XML Representation of Data Mathieu Delalandre¹, Stéphane Nicolas¹, Eric Trupin¹, Jean-Marc Ogier² ¹PSI Laboratory, Rouen University, France ²L3I Laboratory, La Rochelle University, France Phd thesis website: http://site.voila.fr/roxmlhttp://site.voila.fr/roxml

2 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 2 Plan  Structural Shape Recognition  System’s Part I, Graph-Matching  System’s Part II, Global Analysis  System’s Part III, Local Analysis  Scenarios Construction and Use  Experiments and Results  XML Use in System  Conclusion and Perspectives

3 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 3 Plan  Structural Shape Recognition  System’s Part I, Graph-Matching  System’s Part II, Global Analysis  System’s Part III, Local Analysis  Scenarios Construction and Use  Experiments and Results  XML Use in System  Conclusion and Perspectives

4 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 4 Structural Shape Recognition  structural shape recognition, two steps:  structural analysis (Delalandre 2003)  structural recognition (Tombre 1996) Structural Analysis Structural Recognition A B D C

5 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 5 Structural Shape Recognition  applications  oriental handwriting (Lau 2002)  structured document (Naguy 2000)  graphical document (Song 2003)  symbol “structured and graphical document” (Lladós 2001)

6 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 6 Structural Shape Recognition  structural recognition  graph-matching approach (Hancock 2002)  grammar approach (Blostein 1995)  structural analysis (Delalandre 2003)  global & local approaches   multi representation   process simplification localglobal

7 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 7 Plan  Structural Shape Recognition  System’s Part I, Graph-Matching  System’s Part II, Global Analysis  System’s Part III, Local Analysis  Scenarios Construction and Use  Experiments and Results  XML Use in System  Conclusion and Perspectives

8 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 8 System’s Part I, Graph-Matching  exact and inexact graph algorithms  (Héroux 2000)  exact and inexact subgraph algorithms  Ullman’s method (Ullman 1976)  clique based detection method  exact VF methods (Foggia 2001)  exact and inexact Messmer’s decomposition methods (Messmer 1995)

9 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 9 Plan  Structural Shape Recognition  System’s Part I, Graph-Matching  System’s Part II, Global Analysis  System’s Part III, Local Analysis  Scenarios Construction and Use  Experiments and Results  XML Use in System  Conclusion and Perspectives

10 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 10  global analysis based on statistical recognition result use (Delalandre 2002) System’s Part II, Global Analysis

11 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 11 System’s Part II, Global Analysis statistical classification global analysis connected component filtering loop extraction feature extraction image processings recognition processings (1) (5) (4) (3) (2) graphs

12 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 12 System’s Part II, Global Analysis  (1) loop extraction, (2) connected component filtering

13 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 13 System’s Part II, Global Analysis  (3) feature extraction, (4) statistical recognition

14 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 14 System’s Part II, Global Analysis  (5) global analysis  distance and/or closeness constraints   grouping or segmentation strategy

15 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 15 Plan  Structural Shape Recognition  System’s Part I, Graph-Matching  System’s Part II, Global Analysis  System’s Part III, Local Analysis  Scenarios Construction and Use  Experiments and Results  XML Use in System  Conclusion and Perspectives

16 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 16 System’s Part III, Local Analysis  vectorisation scenario, three levels: image levelskeletonisation adaptation contours detection, skeletonisation object simplification, pixel list extraction structured data level interiority degree segmentation, post correction junction and graph construction, vectorisation, curve and arc fitting boundary level

17 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 17 System’s Part III, Local Analysis  image level  a) skeletonisation (Di Baja 1992) & contouring  b) skeletonisation adaptation

18 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 18 System’s Part III, Local Analysis  boundary level  a) pixel list extraction based on 3-connected destruction  b) object simplification (Song 2002)

19 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 19 System’s Part III, Local Analysis  structured data level (1)  a) interiority segmentation  b) polygonisation (Ramer 1972) (Pavlidis 1986), and circle fitting  c) curve fitting (Liao 1990)

20 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 20 System’s Part III, Local Analysis  structured data level (2)  (a-b) node detection  (b-c) Pruning and (c-d) Merging

21 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 21 Plan  Structural Shape Recognition  System’s Part I, Graph-Matching  System’s Part II, Global Analysis  System’s Part III, Local Analysis  Scenarios Construction and Use  Experiments and Results  XML Use in System  Conclusion and Perspectives

22 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 22 Scenario Construction and Use  system based on scenario use (Saïdali 2003)  interface package  scenario construction and execution  statistical learning and structural model acquisition  Knowledge base  training sets  scenarios  entry data  processings library  image processings “local and global”  classification processings

23 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 23 Plan  Structural Shape Recognition  System’s Part I, Graph-Matching  System’s Part II, Global Analysis  System’s Part III, Local Analysis  Scenarios Construction and Use  Experiments and Results  XML Use in System  Conclusion and Perspectives

24 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 24 Experiments and Results  symbol recognition on technical drawing  65 scenarios: different strategies and parameter settings  700 symbol graphs nearest symbols case

25 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 25 Experiments and Results  global strategies (1, 2, 3) 3-grouping +subgraph 100%incoherent 1-segmentation + graph 100% 100% of statistical results49% of statistical resultsstrategy 86.6% 2-segmentation + subgraph 100%46.8% strategy 1 gives good result, but don’t deal the nearest symbols

26 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 26 Experiments and Results  global local strategy (4)  circle erasing + images subtraction + strategy 1 -=

27 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 27 Experiments and Results 3-grouping subgraph 100%Incoherent 1-segmentation graph 100% 100% of statistical results49% of statistical resultsStrategy 86.6% 2-segmentation subgraph 100%46.8% 4-local-global100%87.5% Strategy 4 gives good result and deals the nearest symbols

28 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 28 Experiments and Results  local strategy (5)  circle erasing + skeleton graph + subgraph   room detection   connected characters detection

29 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 29 Plan  Structural Shape Recognition  System’s Part I, Graph-Matching  System’s Part II, Global Analysis  System’s Part III, Local Analysis  Scenarios Construction and Use  Experiments and Results  XML Use in System  Conclusion and Perspectives

30 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 30 XML Use in System  sub-language use  SVG for graphics representations  XGMML for graph library  transformation and request use  XSLT to transform  Quilt to request

31 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 31 Plan  Structural Shape Recognition  System’s Part I, Graph-Matching  System’s Part II, Global Analysis  System’s Part III, Local Analysis  Scenarios Construction and Use  Experiments and Results  XML Use in System  Conclusion and Perspectives

32 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 32 Conclusion and Perspectives  Conclusion  local approach helps global approach  scenario use permits system’s adaptation and strategy test  XML use permits an easy data manipulation  Perspectives  local approach (Delalandre 2003)  result coherency test with RuleML  Knowledge base structuring with RDF

33 ICISP’2003 : Agadir, Morocco : 24 June, 2003Diapo 33 End  sorry for my absent, any question ?  Mail:mathieu.delalandre@univ-rouen.frmathieu.delalandre@univ-rouen.fr  Phd Website:http://site.voila.fr/roxmlhttp://site.voila.fr/roxml

Download ppt "FRE 2645 ICISP’2003 : Agadir, Morocco : 24 June, 2003 Symbol Recognition by Global Local Structural Approaches, Based on Scenario Use, and with a XML Representation."

Similar presentations

MADONNE MAsses de DONnées issues de la Numérisation du patrimoiNE Project Leader : Jean-Marc OGIER L3i Laboratory, la Rochelle University Tel : 0033 5.

MADONNE MAsses de DONnées issues de la Numérisation du patrimoiNE Project Leader : Jean-Marc OGIER L3i Laboratory, la Rochelle University Tel :
Document Examiner Feature Extraction: Thinned vs Skeletonised Images

Document Examiner Feature Extraction: Thinned vs Skeletonised Images
Employing structural representation for symbol detection, symbol spotting and indexation in line drawing document images Muhammad Muzzamil Luqman

Employing structural representation for symbol detection, symbol spotting and indexation in line drawing document images Muhammad Muzzamil Luqman
FRE 2645 GREC 2003 : 31 July 2003 Local Structural Analysis: a Primer Mathieu Delalandre¹, Eric Trupin¹, Jean-Marc Ogier² ¹PSI Laboratory, Rouen University,

FRE 2645 GREC 2003 : 31 July 2003 Local Structural Analysis: a Primer Mathieu Delalandre¹, Eric Trupin¹, Jean-Marc Ogier² ¹PSI Laboratory, Rouen University,
FRE 2645 Graph based Representation 2005 Graphical Knowledge Management in Graphics Recognition Systems Mathieu Delalandre¹, Eric Trupin¹, Jacques Labiche¹,

FRE 2645 Graph based Representation 2005 Graphical Knowledge Management in Graphics Recognition Systems Mathieu Delalandre¹, Eric Trupin¹, Jacques Labiche¹,
Image Processing and Interpretation Group University of Nottingham Eureka Meeting, L3i Laboratory, La Rochelle University Tuesday 20th April 2006 Fast.

Image Processing and Interpretation Group University of Nottingham Eureka Meeting, L3i Laboratory, La Rochelle University Tuesday 20th April 2006 Fast.
Chapter 9: Morphological Image Processing

Chapter 9: Morphological Image Processing
A Robust Approach for Local Interest Point Detection in Line-Drawing Images 1 The Anh Pham, Mathieu Delalandre, Sabine Barrat and Jean-Yves Ramel RFAI.

A Robust Approach for Local Interest Point Detection in Line-Drawing Images 1 The Anh Pham, Mathieu Delalandre, Sabine Barrat and Jean-Yves Ramel RFAI.
Image Segmentation some examples Zhiqiang wang zwang22@kent.edu.

Image Segmentation some examples Zhiqiang wang
On Constrained Optimization Approach To Object Segmentation Chia Han, Xun Wang, Feng Gao, Zhigang Peng, Xiaokun Li, Lei He, William Wee Artificial Intelligence.

On Constrained Optimization Approach To Object Segmentation Chia Han, Xun Wang, Feng Gao, Zhigang Peng, Xiaokun Li, Lei He, William Wee Artificial Intelligence.
Object Detection by Matching Longin Jan Latecki. Contour-based object detection Database shapes: …..

Object Detection by Matching Longin Jan Latecki. Contour-based object detection Database shapes: …..
FRE 2645 SCSIT Talk, Nottingham University, Thursday 16th June 2005 Indexing of Graphic Document Images : a Perceptive Approach Mathieu Delalandre¹, ².

FRE 2645 SCSIT Talk, Nottingham University, Thursday 16th June 2005 Indexing of Graphic Document Images : a Perceptive Approach Mathieu Delalandre¹, ².
ICIP 2000, Vancouver, Canada IVML, ECE, NTUA Face Detection: Is it only for Face Recognition?  A few years earlier  Face Detection Face Recognition 

ICIP 2000, Vancouver, Canada IVML, ECE, NTUA Face Detection: Is it only for Face Recognition?  A few years earlier  Face Detection Face Recognition 
Tuesday, 13th November 2007 Work Group CALYPOD graphiCs imAge anaLYsis from Printed Old Document Presented by.

Tuesday, 13th November 2007 Work Group CALYPOD graphiCs imAge anaLYsis from Printed Old Document Presented by.
Complex Networks for Representation and Characterization of Object For CS790g Project Bingdong Li 11/9/2009.

Complex Networks for Representation and Characterization of Object For CS790g Project Bingdong Li 11/9/2009.
COMP322/S2000/L181 Pre-processing: Smooth a Binary Image After binarization of a grey level image, the resulting binary image may have zero’s (white) and.

COMP322/S2000/L181 Pre-processing: Smooth a Binary Image After binarization of a grey level image, the resulting binary image may have zero’s (white) and.
A new face detection method based on shape information Pattern Recognition Letters, 21 (2000) 463-471 Speaker: M.Q. Jing.

A new face detection method based on shape information Pattern Recognition Letters, 21 (2000) Speaker: M.Q. Jing.
Automated Detection and Characterization of Solar Filaments and Sigmoids K. Wagstaff, D. M. Rust, B. J. LaBonte and P. N. Bernasconi Johns Hopkins University.

Automated Detection and Characterization of Solar Filaments and Sigmoids K. Wagstaff, D. M. Rust, B. J. LaBonte and P. N. Bernasconi Johns Hopkins University.
Prénom Nom Document Analysis: Segmentation & Layout Analysis Prof. Rolf Ingold, University of Fribourg Master course, spring semester 2008.

Prénom Nom Document Analysis: Segmentation & Layout Analysis Prof. Rolf Ingold, University of Fribourg Master course, spring semester 2008.
Processing Digital Images. Filtering Analysis –Recognition Transmission.

Processing Digital Images. Filtering Analysis –Recognition Transmission.

Similar presentations

Ads by Google