A powerful and flexible technique to identify, classify and process documents using images from a scanning process is presented. The types of documents can be described to the system as a set of differentiating features in a case base using shape trees. The features are filtered and abstracted from an extremely reduced scanner image of the document. Classification rules are stored with the case...

In the previous chapters, we proposed several features for writer identification, historical manuscript dating and localization separately. In this chapter, we present a summarization of the proposed features for different applications by proposing a joint feature distribution (JFD) principle to design novel discriminative features which could be the joint distribution of features on adjacent p...

Optical Character Recognition (OCR) is a process to recognize the handwritten or printed scanned text with the help of a computer. Segmentation is very important stage of any text recognition system. The problems in segmentation can lead to decrease in segmentation rate and hence recognition rate. A good segmentation technique can improve the recognition rate. This paper deals with the hazards ...

Working with Optical Character Recognition for the printed Gurmukhi Script is a challenging task due to the large number of characters, the sophisticated ways in which they combine, and the complicated result. This paper describes a fast and easy to implement algorithm for detection of bold and italic character in Gurmukhi Script. The algorithm works without recognition of actual character and ...

The classification of digital documents is a complex task in a document analysis flow. The amount of documents resulting from the OCR retro-conversion (optical character recognition) makes the classification task harder. In the literature, different features are used to improve the classification quality. In this paper, we evaluate various features on OCRed and non OCRed documents. Thanks to th...

Previous research efforts on optical font recognition have mostly limited applications since they deal with only a few types of font attributes and estimate them from a line or block of text. This paper proposes a word-level optical font recognition system for printed Korean and English documents. At the word-level, it has the advantages of obtaining more detailed font attributes including the ...

The working module of any Optical character Recognition system almost depends upon printing and paper of the input document image. A number of OCR techniques are available and claim correctly identified accuracy in printed document image in Indian and foreign script. A few report have been found on the recognition of the degraded Indian language document. The degradation in any scanned printed ...

Electronic Document Management (EDM) technology is being widely adopted as it makes for the efficient routing and retrieval of documents. Optical Character Recognition (OCR) is an important front end for such technology. Excellent OCR now exists for Latin based languages, but there are few systems that read Arabic, which limits the penetration of EDM into Arabicspeaking countries. In developing...