1. FRE 2645 ELCVIA Contextual System of Symbol Structural Recognition based on an Object-Process Methodology Mathieu Delalandre¹, Eric Trupin¹, Jean-Marc Ogier², Jacques Labiche¹ ¹ Laboratoire PSI, Université de Rouen ² Laboratoire L3I, Université de La Rochelle

2. ELCVIA Introduction (1) Symbol Recognition utility mapelectrical drawingarchitectural drawing some symbols

3. ELCVIA Introduction (2) Problem of Context : Examples noise size of symbol set near segmentation problem

4. ELCVIA Introduction (3) Our Approach Control System Processings Knowledge Base Object-Process Methodology based Structuring graphics primitives (objects) & context evaluation strategy control object process Machine Man Interfaces Contextual System of Symbol Structural Recognition based on an Object- Process Methodology uses a object building strategy  this one concerns the interactions between objects during the building process in order to simplify the considered recognition problem.

5. ELCVIA Contextual System (1) Graphic Primitive Extraction region based skeleton based

6. ELCVIA Contextual System (2) Building Objects skeletonization and chaining + polygonisation and arc fitting region graph extraction + statistical recognition of loops merging

7. ELCVIA Contextual System (3) Rule based System for OPM  Knowledge base : {F, P, Q}  F : fact base  R : rule base  Q : request  Rule : {Pr, O, S, R}  {Pr} Processing  {O} Object(s)  {S} Setting(s)  {R} Rule(s) “fact to update”

8. ELCVIA Knowledge Base Processings Contextual System (4) Rule based System for OPM rsOPM Objects and Rules Rules Objects

9. ELCVIA Contextual System (5) XML graphics model learning ELCVIA2004.avi

10. ELCVIA Use Case (1) Introduction  Symbol Contest of GREC’03:  20 classes of architectural and electrical symbol  9 sets of 100 noised images

11. ELCVIA Use Case (2) Contextual Pre-Processing  Pre-processing using 10 rules according to the noise evaluation  eroded (e), valid (v), dilated (d)  Sparse (s), no sparse (ns)  Operators of filtering:  dilating (dp)  opening/closing “low filtering” (lfp)  component filtering “filtering” (fp)  eroding (ep) sparse noisemorphological noise (v,s)  fp(e,s)  lfp(e,ns)  dp

12. ELCVIA Use Case (3) Building Objects first step : region graph second step : having similar graph, + statistical recognition of loops

13. ELCVIA Use Case (4) Building Strategy Sym1 (Aa, Ae, Ah, Eb, Ee)Node01 (Ec, Ed, Ef, Eh) Node02 (Ac, Ad, Ai, Ea, Eg, Ei)Node04 (Ab, Af, Ag, Aj, Ej)

14. ELCVIA Use Case (5) Results of OPM/no OPM (direct)