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Unformatted text preview: AN ALGORITHM USING WALSH TRANSFORMATION FOR COMPRESSING TYPESET DOCUMENTS Attila Fazekas and Andr´ as Hajdu [email protected] [email protected] Lajos Kossuth University 4010, Debrecen PO Box 12, Hungary Dedicated to L. Hajdu on the occasion of his 30th birthday. Abstract. In this paper the authors present an algorithm which can be used for compressing text documents, principally. The algorithm allows some loss of infor mation, but the original digital image is compressed in a rather efficient way, so the result compressed data structure is suitable to be transmitted through some kind of telecommunication channel. The original document is assumed not to contain sophis ticated typographical details, but text, and some simple graphics. The compression algorithm tries to recognize the text parts of the document and the result of a char acter recognition process is stored, instead of the graphic representation of the text. This character recognition part is based on Walsh transformation. The algorithm was tested in several cases, and proved itself to be pretty efficient and reliable for simple documents. Keywords. Image data compression, optical character recognition, Walsh transfor mation AMS Subject Classification. 68U10 Image Processing 1. INTRODUCTION One of the basic problems in digital image processing is to use minimal memory to store the data structure which represents the digital image. An algorithm is called compressive if it assigns a data structure P to the original digital image P so that less memory is required to store P than P . Several compressive algorithms are known which are based on different methods. Be side the ordinal data compressors, when we do not care what sort of information the data structure represents, there are some algorithms which were developed especially for compressing digital images (or a special type of digital images). The efficiency of the compression is usually defined by the value  P   P  , where  P  is the size of the data structure P . An algorithm is more efficient if the compressed data structure reserves less memory than the original image. In our terminology, the best algorithm is a not necessarily unique one which gives the most efficient compression for a given digital image. Obviously, it is not sure that the best algorithm remains the most efficient one if we consider another image. It is extremely difficult to find out which compressive algorithm is the best for the digital images we are about to process. The authors in the literature propose several algorithms according to the characteristics of the digital images. For example, an algorithm for compressing line drawings can be found in [3], or if you are looking for a survey on compression algorithms, see [2]....
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This note was uploaded on 02/04/2012 for the course COMPUTER 101 taught by Professor Ahmed during the Spring '11 term at alamo.edu.
 Spring '11
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