Technical Section: Using data mining for digital ink recognition: Dividing text and shapes in sketched diagrams

Authors:
Rachel Blagojevic;Beryl Plimmer;John Grundy;Yong Wang
Affiliations:
University of Auckland, Private bag 92019, Auckland, New Zealand;University of Auckland, Private bag 92019, Auckland, New Zealand;Swinburne University of Technology, PO Box 218, Hawthorn, Victoria 3122, Australia;University of Auckland, Private bag 92019, Auckland, New Zealand
Venue:
Computers and Graphics
Year:
2011

Citing 39
Cited 3

Learning internal representations by error propagation

Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
Very Simple Classification Rules Perform Well on Most Commonly Used Datasets

Machine Learning
Bagging predictors

Machine Learning
Wrappers for feature subset selection

Artificial Intelligence - Special issue on relevance
On Combining Classifiers

IEEE Transactions on Pattern Analysis and Machine Intelligence
Classification by pairwise coupling

NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Random Forests

Machine Learning
A domain-independent system for sketch recognition

Proceedings of the 1st international conference on Computer graphics and interactive techniques in Australasia and South East Asia
Multiclass Alternating Decision Trees

ECML '02 Proceedings of the 13th European Conference on Machine Learning
An adaptation of Relief for attribute estimation in regression

ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
An interactive system for recognizing hand drawn UML diagrams

CASCON '00 Proceedings of the 2000 conference of the Centre for Advanced Studies on Collaborative research
Structure in On-line Documents

ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Discerning Structure from Freeform Handwritten Notes

ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Sketched Symbol Recognition using Zernike Moments

ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Hierarchical parsing and recognition of hand-sketched diagrams

Proceedings of the 17th annual ACM symposium on User interface software and technology
Contextual Recognition of Hand-Drawn Diagrams with Conditional Random Fields

IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Distinguishing Text from Graphics in On-Line Handwritten Ink

IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Logistic Model Trees

Machine Learning
Diagram Structure Recognition by Bayesian Conditional Random Fields

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Structuralizing digital ink for efficient selection

Proceedings of the 11th international conference on Intelligent user interfaces
Improvements to Platt's SMO Algorithm for SVM Classifier Design

Neural Computation
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Connector semantics for sketched diagram recognition

AUIC '07 Proceedings of the eight Australasian conference on User interface - Volume 64
Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes

Proceedings of the 20th annual ACM symposium on User interface software and technology
Properties of Real-World Digital Logic Diagrams

PLT '07 Proceedings of the First International Workshop on Pen-Based Learning Technologies
PaleoSketch: accurate primitive sketch recognition and beautification

Proceedings of the 13th international conference on Intelligent user interfaces
Temporal sketch recognition in interspersed drawings

SBIM '07 Proceedings of the 4th Eurographics workshop on Sketch-based interfaces and modeling
Ink features for diagram recognition

SBIM '07 Proceedings of the 4th Eurographics workshop on Sketch-based interfaces and modeling
Lineogrammer: creating diagrams by drawing

Proceedings of the 21st annual ACM symposium on User interface software and technology
A toolkit approach to sketched diagram recognition

BCS-HCI '07 Proceedings of the 21st British HCI Group Annual Conference on People and Computers: HCI...but not as we know it - Volume 1
Automatic evaluation of sketch recognizers

Proceedings of the 6th Eurographics Symposium on Sketch-Based Interfaces and Modeling
Computational Support for Sketching in Design: A Review

Foundations and Trends in Human-Computer Interaction
Using entropy to distinguish shape versus text in hand-drawn diagrams

IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
A visual approach to sketched symbol recognition

IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Technical Section: The effect of task on classification accuracy: Using gesture recognition techniques in free-sketch recognition

Computers and Graphics
Feature extraction and classifier combination for image-based sketch recognition

Proceedings of the Seventh Sketch-Based Interfaces and Modeling Symposium
The power of automatic feature selection: Rubine on steroids

Proceedings of the Seventh Sketch-Based Interfaces and Modeling Symposium
Speeding up logistic model tree induction

PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
A data collection tool for sketched diagrams

SBM'08 Proceedings of the Fifth Eurographics conference on Sketch-Based Interfaces and Modeling

RATA: codeless generation of gesture recognizers

BCS-HCI '12 Proceedings of the 26th Annual BCS Interaction Specialist Group Conference on People and Computers
Supervised machine learning for grouping sketch diagram strokes

Proceedings of the International Symposium on Sketch-Based Interfaces and Modeling
Technical Section: A machine learning approach to automatic stroke segmentation

Computers and Graphics

Quantified Score

Hi-index	0.00

Visualization

Abstract

The low accuracy rates of text-shape dividers for digital ink diagrams are hindering their use in real world applications. While recognition of handwriting is well advanced and there have been many recognition approaches proposed for hand drawn sketches, there has been less attention on the division of text and drawing ink. Feature based recognition is a common approach for text-shape division. However, the choice of features and algorithms are critical to the success of the recognition. We propose the use of data mining techniques to build more accurate text-shape dividers. A comparative study is used to systematically identify the algorithms best suited for the specific problem. We have generated dividers using data mining with diagrams from three domains and a comprehensive ink feature library. The extensive evaluation on diagrams from six different domains has shown that our resulting dividers, using LADTree and LogitBoost, are significantly more accurate than three existing dividers.