Dutch Forensic Institute
♦ Artificial Intelligence Institute
University of Groningen
* Nijmegen Institute for Cognition and
Information
Radboud University Nijmegen
Introducing TRIGRAPHtrimodal writer identification
Ralph Niels*, Louis Vuurpijl*and Lambert Schomaker♦
ENFHEX conference - November 2005 – Budapest, Hungary
Overview
● Computer assisted document examination● TRIGRAPH combines 3 methods:
I Automatic features from imageII Manually measured propertiesIII Allographic features
● Recent achievement: “intuitive” matching● Summary● Next steps
Computer assisted document examination
Computer assisted document examination
Improving on current systems
● Systems do not benefit from recent advances in pattern recognition and image processing
● New insights in:– automatically derived
handwriting features– user interface development– innovations in forensic writer identification systems
● Aim: Suspected document in top-100 hit list from database of > 20,000 writers
Design requirements
● Improve on currently available performance● Minimize amount of manual labor● Exploit human cognition and expertise● Correspond to expectations of human experts
WANDA
● Integrate techniques in WANDA Workbench(Franke et al., ENFHEX News 2004; Van Erp et al., JFDE (16) 2004)
Three approaches
I Automatic features from images
II Manually measured properties
III Allographic features
Automatic features from images (1)● Layout and spacing
● Ink morphology
(Franke)
I
Automatic features from images (2)● Local shape (Bulacu)
I
Automatic features from images (3)● Grapheme-fraglet tables (Schomaker)
I
Manually measured propertiesII
●Fish●Script●Wanda
Allographic properties (1)● (Vuurpijl, Niels) Matching characters by:
– Considering global shape characteristics
– Reconstructing and comparing production process
– Zooming in on particular features
III
“Intuitive” matching (1)
● Given: 2 dynamic trajectories(one questioned, one from aset of prototypes)
● Technique: Dynamic TimeWarping (point-to-pointcomparison)
● Result: similarity measure thatcan be used to find prototypethat is most similar toquestioned sample
1
10
1
7
III
“Intuitive” matching (2)● Experiment: compare various techniques
● Result: Dynamic Time Warping yields visually convincing (or “intuitive”) results
● Our work on DTW was previously presented at:● 9th International Workshop on Frontiers in Handwriting Recognition
(IWFHR-2004), Japan. ● 12th Conference of the International Graphonomics Society
(IGS-2005), Italy.● 8th International Conference on Document Analysis and Recognition
(ICDAR-2005), South-Korea.
III
Allographic properties (2)● (Semi-)automatic extraction of dynamic information:
– Automatically extract traces from scanned document– Verify resulting trajectories with allograph prototypes– Start user-interaction in case of confusion
● Advantages:– More reliable measurements– Online character recognition techniques– Search for particular allographs in documents– Visually convincing matching techniques
III
Summary● Computers can help forensic experts in measuring
handwriting and searching databases
● In TRIGRAPH, new insights from different scientific areas will be used
● In TRIGRAPH, new UI methods will be combined with techniques developed in three modalities:
I Automatic features from images
II Manually measured properties
III Allographic features
Next steps
● Automatic extraction of dynamical information from scanned images
● Supervised character segmentation
● Allograph based verification of results
♦ Artificial Intelligence Institute
University of Groningen
Dutch Forensic Institute
* Nijmegen Institute for Cognition and
Information
Radboud University Nijmegen
Introducing TRIGRAPHtrimodal writer identification
Ralph Niels*, Louis Vuurpijl*and Lambert Schomaker♦
ENFHEX conference - November 2005 – Budapest, Hungary
