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%.

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%.

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%.