9,993 research outputs found
Kannada Character Recognition System A Review
Intensive research has been done on optical character recognition ocr and a
large number of articles have been published on this topic during the last few
decades. Many commercial OCR systems are now available in the market, but most
of these systems work for Roman, Chinese, Japanese and Arabic characters. There
are no sufficient number of works on Indian language character recognition
especially Kannada script among 12 major scripts in India. This paper presents
a review of existing work on printed Kannada script and their results. The
characteristics of Kannada script and Kannada Character Recognition System kcr
are discussed in detail. Finally fusion at the classifier level is proposed to
increase the recognition accuracy.Comment: 12 pages, 8 figure
Electronic marking and identification techniques to discourage document copying
Modern computer networks make it possible to distribute documents quickly and economically by electronic means rather than by conventional paper means. However, the widespread adoption of electronic distribution of copyrighted material is currently impeded by the ease of illicit copying and dissemination. In this paper we propose techniques that discourage illicit distribution by embedding each document with a unique codeword. Our encoding techniques are indiscernible by readers, yet enable us to identify the sanctioned recipient of a document by examination of a recovered document. We propose three coding methods, describe one in detail, and present experimental results showing that our identification techniques are highly reliable, even after documents have been photocopied
Component-based Segmentation of words from handwritten Arabic text
Efficient preprocessing is very essential for automatic recognition of handwritten documents. In this paper, techniques on segmenting words in handwritten Arabic text are presented. Firstly, connected components (ccs) are extracted, and distances among different components are analyzed. The statistical distribution of this distance is then obtained to determine an optimal threshold for words segmentation. Meanwhile, an improved projection based method is also employed for baseline detection. The proposed method has been successfully tested on IFN/ENIT database consisting of 26459 Arabic words handwritten by 411 different writers, and the results were promising and very encouraging in more accurate detection of the baseline and segmentation of words for further recognition
A robust braille recognition system
Braille is the most effective means of written communication between
visually-impaired and sighted people. This paper describes a new system
that recognizes Braille characters in scanned Braille document pages. Unlike
most other approaches, an inexpensive flatbed scanner is used and the system
requires minimal interaction with the user. A unique feature of this system is
the use of context at different levels (from the pre-processing of the image
through to the post-processing of the recognition results) to enhance robustness
and, consequently, recognition results. Braille dots composing characters are
identified on both single and double-sided documents of average quality with
over 99% accuracy, while Braille characters are also correctly recognised in
over 99% of documents of average quality (in both single and double-sided
documents)
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