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Document Image Analysis, like any Digital Image Analysis requiresidentification and extraction of proper features, which are generally extractedfrom uncompressed images, though in reality images are made available incompressed form for the reasons such as transmission and storage efficiency.However, this implies that the compressed image should be decompressed, whichindents additional computing resources. This limitation induces the motivationto research in extracting features directly from the compressed image. In thisresearch, we propose to extract essential features such as projection profile,run-histogram and entropy for text document analysis directly from run-lengthcompressed text-documents. The experimentation illustrates that features areextracted directly from the compressed image without going through the stage ofdecompression, because of which the computing time is reduced. The featurevalues so extracted are exactly identical to those extracted from uncompressedimages.

Extraction of Projection Profile, Run-Histogram and Entropy Features Straight from Run-Length Compressed Text-Documents