Chinese Handwriting Recognition: An Algorithmic Perspective
By: by Tonghua Su
Contributors: SpringerLink (Online service)
Series: SpringerBriefs in Electrical and Computer Engineering
Publisher: Springer Berlin Heidelberg; Imprint: Springer
Published: 2013
Place of publication: Berlin, Heidelberg
Language: eng
Format: [electronic resource] /
Number of pages: 124
ISBN-13: 9783642318122
Subjects: Computer Imaging, Vision, Pattern Recognition and Graphics; Pattern perception; Image Processing and Computer Vision; Computer science; Optical pattern recognition; Computer vision
Description: <p>This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focused on. Baseline systems are initially presented for these strategies and are subsequently expanded on and incrementally improved. The sophisticated algorithms covered include: 1) string sample expansion algorithms which synthesize string samples from isolated characters or distort realistic string samples; 2) enhanced feature representation algorithms, e.g. enhanced four-plane features and Delta features; 3) novel learning algorithms, such as Perceptron learning with dynamic margin, MPE training and distributed training; and lastly 4) ensemble algorithms, that is, combining the two strategies using both parallel structure and serial structure. All the while, the book moves from basic to advanced algorithms, helping readers quickly embark on the study of Chinese handwriting recognition.</p>
Table of contents: title: Introduction; title: HIT-MW Database; title: Integrated Segmentation-Recognition Strategy; title: Segmentation-free Strategy: Basic Algorithms; title: Segmentation-free Strategy: Advanced Algorithms.