A skip-line with threshold algorithm for binary image compression

Binary images (Bi-level images; Bi-Color images, Two-tone images or Monochrome images) have been widely used in image processing, such as facsimile, letters, map archives, digital libraries, fingerprint databases, and those documents that could not be recognized by OCR. In order to reduce the storage space of binary images, there are many researchers attempted to propose more efficient algorithms for binary image compression. In general, they can be divided into two kinds of methods which are ‘lossless’ and ‘lossy’. In this research, we base on a lossy image compression method, to propose a compression Algorithm called “Skip-Line Encoding with Threshold” (SLETA). Our results of experiments show that SLETA not only achieve high compression ratio but also keep good recognizability: encoded images are not difficult to recognize after decompressions.

[1]  Lele Zhou,et al.  A New Efficient Algorithm for Lossless Binary Image Compression , 2006, 2006 Canadian Conference on Electrical and Computer Engineering.

[2]  Richard W. Hamming,et al.  Coding and Information Theory , 1980 .

[3]  Charles G. Boncelet,et al.  An algorithm for compression of bilevel images , 2001, IEEE Trans. Image Process..

[4]  Anil K. Jain.  Fundamentals of Digital Image Processing , 2018, Control of Color Imaging Systems.

[5]  S. Zahir,et al.  A new rectangular partitioning based lossless binary image compression scheme , 2005, Canadian Conference on Electrical and Computer Engineering, 2005..

[6]  R. Chowdhury,et al.  A Hybrid 2-3-3 Bits-Based Image Encoding Scheme , 2006, 2006 IEEE International Symposium on Signal Processing and Information Technology.

[7]  Jerry D. Gibson,et al.  Digital coding of waveforms: Principles and applications to speech and video , 1985, Proceedings of the IEEE.

[8]  Athar Ali Moinuddin,et al.  An efficient technique for storage of two-tone images , 1997 .

[9]  Moustafa M. Fahmy,et al.  Binary image compression using efficient partitioning into rectangular regions , 1995, IEEE Trans. Commun..

[10]  Saif Zahir,et al.  A near minimum sparse pattern coding based scheme for binary image compression , 2005, IEEE International Conference on Image Processing 2005.