Empirical Performance Evaluation of Graphics Recognition Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
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
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Handwritten Numeral String Recognition: Character-Level vs. String-Level Classifier Training
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
IEEE Transactions on Pattern Analysis and Machine Intelligence
Grouping Text Lines in Freeform Handwritten Notes
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
Text/Non-text Ink Stroke Classification in Japanese Handwriting Based on Markov Random Fields
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
On-Line Handwritten Text Line Detection Using Dynamic Programming
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
Learning to Group Text Lines and Regions in Freeform Handwritten Notes
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
Online Handwritten Japanese Character String Recognition Incorporating Geometric Context
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
DAS '08 Proceedings of the 2008 The Eighth IAPR International Workshop on Document Analysis Systems
Sketch-based interfaces: exploiting spatio-temporal context for automatic stroke grouping
SG'10 Proceedings of the 10th international conference on Smart graphics
An approach for real-time recognition of online Chinese handwritten sentences
Pattern Recognition
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In this paper, we present an effective approach for grouping text lines in online handwritten Japanese documents by combining temporal and spatial information. With decision functions optimized by supervised learning, the approach has few artificial parameters and utilizes little prior knowledge. First, the strokes in the document are grouped into text line strings according to off-stroke distances. Each text line string, which may contain multiple lines, is segmented by optimizing a cost function trained by the minimum classification error (MCE) method. At the temporal merge stage, over-segmented text lines (caused by stroke classification errors) are merged with a support vector machine (SVM) classifier for making merge/non-merge decisions. Last, a spatial merge module corrects the segmentation errors caused by delayed strokes. Misclassified text/non-text strokes (stroke type classification precedes text line grouping) can be corrected at the temporal merge stage. To evaluate the performance of text line grouping, we provide a set of performance metrics for evaluating from multiple aspects. In experiments on a large number of free form documents in the Tokyo University of Agriculture and Technology (TUAT) Kondate database, the proposed approach achieves the entity detection metric (EDM) rate of 0.8992 and the edit-distance rate (EDR) of 0.1114. For grouping of pure text strokes, the performance reaches EDM of 0.9591 and EDR of 0.0669.