Recognition of whiteboard notes: online, offline and combination

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Series: Machine Perception and Artificial Intelligence

ISBN: 9789812814531, 9812814531

Size: 4 MB (4487785 bytes)

Pages: 227/227

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Marcus Liwicki, Horst Bunke9789812814531, 9812814531

This book addresses the task of processing online handwritten notes acquired from an electronic whiteboard, which is a new modality in handwriting recognition research. The main motivation of this book is smart meeting rooms, aim to automate standard tasks usually performed by humans in a meeting.
The book can be summarized as follows. A new online handwritten database is compiled, and four handwriting recognition systems are developed. Moreover, novel preprocessing and normalization strategies are designed especially for whiteboard notes and a new neural network based recognizer is applied. Commercial recognition systems are included in a multiple classifier system. The experimental results on the test set show a highly significant improvement of the recognition performance to more than 86%.
Contents: Classification Methods; Linguistic Resources and Handwriting Databases; Off-Line Approach; On-Line Approach; Multiple Classifier Combination; Writer-Dependent Recognition.

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