Entropy Computations of Document Images in Run-Length Compressed Domain

Compression of documents, images, audios and videos have been traditionally practiced to increase the efficiency of data storage and transfer. However, in order to process or carry out any analytical computations, decompression has become an unavoidable pre-requisite. In this research work, we have...

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Bibliographic Details
Published in2014 Fifth International Conference on Signal and Image Processing pp. 287 - 291
Main Authors Nagabhushan, P., Javed, Mohammed, Chaudhuri, B. B.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2014
Subjects
compressed documents
compressed domain processing
Data mining
Energy measurement
Entropy
Feature extraction
Image coding
Position measurement
run-length compression
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Summary:Compression of documents, images, audios and videos have been traditionally practiced to increase the efficiency of data storage and transfer. However, in order to process or carry out any analytical computations, decompression has become an unavoidable pre-requisite. In this research work, we have attempted to compute the entropy, which is an important document analytic directly from the compressed documents. We use Conventional Entropy Quantifier (CEQ) and Spatial Entropy Quantifiers (SEQ) for entropy computations [1]. The entropies obtained are useful in applications like establishing equivalence, word spotting and document retrieval. Experiments have been performed with all the data sets of [1], at character, word and line levels taking compressed documents in run-length compressed domain. The algorithms developed are computational and space efficient, and results obtained match 100% with the results reported in [1].
DOI:10.1109/ICSIP.2014.51