Издательство InTech, 2011, -102 pp.
In the field of document recognition and understanding, whereas scanned paper documents were previously the only recognition target, various new media such as camera-captured documents, videos, and natural scene images have recently started to attract attention because of the growth of the Inteet/WWW and the rapid adoption of low-priced digital cameras/videos. The keys to the breakthrough include character detection from complex backgrounds, discrimination of characters from noncharacters, mode or ancient unique font recognition, fast retrieval technique from large-scaled scanned documents, multi-lingual OCR, and unconstrained handwriting recognition. This book aims to present recent advances, applications, and new ideas that are relevant to document recognition and understanding, from technical topics such as image processing, feature extraction or classification, to new applications like camera-based recognition or character-based natural scene analysis. The goal of this book is to provide a new trend and a reference source for academic research and for professionals working in the document recognition and understanding field.
Statistical Deformation Model for Handwritten Character Recognition
Character Recognition with Metasets
Recognition of Tifinaghe Characters Using Dynamic Programming & Neural Network
Character Degradation Model and HMM Word Recognition System for Text Extracted from Maps
Grid’5000 Based Large Scale OCR Using the DTW Algorithm: Case of the Arabic Cursive Writing
Application of Gaussian-Hermite Moments in License
In the field of document recognition and understanding, whereas scanned paper documents were previously the only recognition target, various new media such as camera-captured documents, videos, and natural scene images have recently started to attract attention because of the growth of the Inteet/WWW and the rapid adoption of low-priced digital cameras/videos. The keys to the breakthrough include character detection from complex backgrounds, discrimination of characters from noncharacters, mode or ancient unique font recognition, fast retrieval technique from large-scaled scanned documents, multi-lingual OCR, and unconstrained handwriting recognition. This book aims to present recent advances, applications, and new ideas that are relevant to document recognition and understanding, from technical topics such as image processing, feature extraction or classification, to new applications like camera-based recognition or character-based natural scene analysis. The goal of this book is to provide a new trend and a reference source for academic research and for professionals working in the document recognition and understanding field.
Statistical Deformation Model for Handwritten Character Recognition
Character Recognition with Metasets
Recognition of Tifinaghe Characters Using Dynamic Programming & Neural Network
Character Degradation Model and HMM Word Recognition System for Text Extracted from Maps
Grid’5000 Based Large Scale OCR Using the DTW Algorithm: Case of the Arabic Cursive Writing
Application of Gaussian-Hermite Moments in License