1-D chaincode pattern matching for compression of Bi-level printed farsi and arabic textual images

In some scripts, especially the Farsi/Arabic script, letters normally attach together and produce many different patterns, some of which are fully or partially similar. Detecting such patterns and exploiting them to reduce the library size, has a rather great effect on the compression ratio.In this paper, a lossy/lossless compression method is proposed for bi-level printed text images in archiving applications. For this, we propose a new 1-D pattern matching technique in the chain coding domain that uses the proposed technique of detecting the repetitive sub-signals in order to detect the fully or partially similar patterns.Experimental results show that the compression performance of the proposed method is considerably better than those of the existing bi-level printed text image compression methods as high as 1.8–4.2 times in the lossy case and 1.6–3.8 times in the lossless case at 300 dpi.