Progress In Handwriting Recognition
Will be published approx. on 7. July 1997
Book
Hardback
644 pages
978-981-02-3084-5 (ISBN)
Description
Handwriting Recognition has become a very important research area which is attracting more and more scientists. In fact, the extraordinary advances in the field of data acquisition technology and the promising results of the research, nowadays make possible the development of commercial systems for processing and recognition of handwritten documents.This book contains the results of the activity of the most important academic and industrial research groups working in this area. The new issues arising in the field are focused and involve both theoretical and practical aspects related to handwriting recognition and document processing systems. The contributions of eminent experts point out the more interesting challenges for the scientific community ranging from acquisition and preprocessing of handwritten documents, to recognition of handwritten digits and words, to the design of multi-expert systems and the exploitation of the contextual knowledge to improve system performance.
More details
Language
English
Place of publication
Singapore
Singapore
Target group
College/higher education
Professional and scholarly
Product notice
Laminated cover
Dimensions
Height: 227 mm
Width: 167 mm
Thickness: 33 mm
Weight
1012 gr
ISBN-13
978-981-02-3084-5 (9789810230845)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Content
The role of handwriting recognition in future reading systems, N. Bartneck; improving recognition rates by classifier combination, J. Kittler; recent advances in off-line handwriting recognition, S.N. Srihari; a thalamocortical algorithm that performs handwritten character recognition, B. Alexandrovsky et al; a new approach to handwritten character recognition using multiple experts, A.F. Rahman and M.C. Fairhurst; enrolment validation in optimization of practical signature verification procedures, M.C. Fairhurst and C.C. Allgrove; optimizing handwritten cascade recognition by neural network cascade, A. Amiri et al; writer identification by computer imitating human identification procedure, S. Nozawa and T. Takeshita; improving scanning n-tuple classifiers by pre-transforming training data, S. Lucas; recognition of cursively handwritten words using a combined normalization/perturbation approach, G. Kaufmann et al; processing of data information on cheques, R. Fan et al. (Part contents).