1. Statistical Deformation Model for Handwritten Character Recognition.
2. Recognition of Tifinaghe Characters Using Dynamic Programming & Neural Network.
3. Character Recognition with Metasets.
4. Character Degradation Model and HMM Word Recognition System for Text Extracted from Maps.
5. Grid'5000 Based Large Scale OCR Using the DTW Algorithm: Case of the Arabic Cursive Writing.
6. Application of Gaussian-Hermite Moments in License.

The latest advances and developments in the field of document recognition are comprehensively presented in this extensive book. Camera-captured documents, natural scene images and videos have emerged as the new-age document recognition media due to the development of new media and internet. With the advent of low-priced digital cameras/recorders, they seem to get widely recognized while scanned paper documents were the only recognition target earlier. Advancements in novel techniques such as distinction of characters from non-characters, quick retrieval techniques from large-scaled scanned documents, character detection from complex backgrounds, unconstrained handwriting recognition and multi-lingual OCR among many others have led to breakthroughs in this field. This book serves the objective of presenting new ideas, latest developments and applications of crucial importance in document understanding and recognition. It presents technical topics such as feature classification or extraction, image processing and novel applications such as character-based natural scene analysis and camera-based recognition. This book aims to serve as a valuable reference for academic research and assist professionals in the field of document recognition and understanding.