Advances in Character Recognition

This book presents advances in character recognition, and it consists of 12 chapters that cover wide range of topics on different aspects of character recognition. Hopefully, this book will serve as a reference source for academic research, for professionals working in the character recognition field and for all interested in the subject

Cognitive Information Processing

Contains research objectives and summary of research on eight research projects.Joint Services Electronics Program (Contract DAAB07-74-C-0630)National Science Foundation (Grant GK-33736X2)National Science Foundation (Grant EPP74-12653)National Institutes of Health (Grant 5 P01 GM19428-03)National Institutes of Health (Grant 3 PO1 GM19428-03S1)National Institutes of Health (Grant 5 PO1 GM14940-07)Peter Bent Brigham Hospital Purchase Order G-33196 #2Associated Press (Grant

Aspects of n-tuple character recognition for a blind reading aid

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.This thesis reports research conducted into a character recognition system suitable for use in a reading aid for the blind. A brief review of blind reading aids is given, showing the need for a device which is cheap, simple and effective. The structure of a proposed reading aid fulfilling these needs is outlined, with a list of the desired characteristics of each of its subsystems. The remainder of the thesis is concerned with research into just two of these subsystems: the input device and the character recognizer. A detailed review of pattern recognition by the n-tuple method is presented, followed by a description of the experimental techniques used in obtaining real data from a camera system, and in simulating various recognizer structures. The camera system and computer programs developed specifically for the research are described in detail. Several series of experiments are reported, concerned mainly with investigating problems associated directly with the blind reading aid, namely accommodation of multifont printed text and of the tracking errors inherent in data from a hand-held probe. A further series of experiments, aimed at improving the performance of the recognizer within fixed size constraints, i. e., optimisation, has a wider field of application. Finally suggestions are made as to how the recognizer might be implemented in a reading aid, using RAMs, ROMs, or PLAs as the main storage elements.Science Research Counci

Cognitive Information Processing

Contains research objectives and summary of research.Madeline Moses FundNational Science Foundation (Grant GK-33736X1)National Institutes of Health (Grant 5 PO1 GM19428-02)Peter Bent Brigham Hospital, Purchase Order G-33196Associated Press (Grant)National Institutes of Health (Grant 5 PO1 GM14940-07

NBS monograph

From Introduction: "This report is the first of a series intended to provide a selective overview of research and development efforts and requirements in the somewhat overlapping fields of the computer and information sciences and technologies. The projected series of reports will attempt to outline the probable range of R & D activities in the computer and information sciences and technologies through selective reviews of the literature and to develop a reasonable consensus with respect to the opinions of workers in these and potentially related fields as to areas of continuing R & D concern for research program planning or review in these areas.

A Baybayin word recognition system

Baybayin is a pre-Hispanic Philippine writing system used in Luzon island. With the effort in reintroducing the script, in 2018, the Committee on Basic Education and Culture of the Philippine Congress approved House Bill 1022 or the ”National Writing System Act,” which declares the Baybayin script as the Philippines’ national writing system. Since then, Baybayin OCR has become a field of research interest. Numerous works have proposed different techniques in recognizing Baybayin scripts. However, all those studies anchored on the classification and recognition at the character level. In this work, we propose an algorithm that provides the Latin transliteration of a Baybayin word in an image. The proposed system relies on a Baybayin character classifier generated using the Support Vector Machine (SVM). The method involves isolation of each Baybayin character, then classifying each character according to its equivalent syllable in Latin script, and finally concatenate each result to form the transliterated word. The system was tested using a novel dataset of Baybayin word images and achieved a competitive 97.9% recognition accuracy. Based on our review of the literature, this is the first work that recognizes Baybayin scripts at the word level. The proposed system can be used in automated transliterations of Baybayin texts transcribed in old books, tattoos, signage, graphic designs, and documents, among others

A Font Search Engine for Large Font Databases

A search engine for font recognition is presented and evaluated. The intended usage is the search in very large font databases. The input to the search engine is an image of a text line, and the output is the name of the font used when rendering the text. After pre-processing and segmentation of the input image, a local approach is used, where features are calculated for individual characters. The method is based on eigenimages calculated from edge filtered character images, which enables compact feature vectors that can be computed rapidly. In this study the database contains 2763 different fonts for the English alphabet. To resemble a real life situation, the proposed method is evaluated with printed and scanned text lines and character images. Our evaluation shows that for 99.1% of the queries, the correct font name can be found within the five best matches