Asian Journal of Computer Science and Technology (AJCST)
An Enhanced Technique for Fractal Image Compression Using Block Based Features (BBF)Author : Dr. T. Velumani, A. R. Karthekeyan and R. Saveetha
Volume 8 No.2 April-June 2019 pp 90-97
Image Compression is very active research area specializing on how to compression and decompression of images. The various methods have been proposed for fractal image compression techniques for storage and drawbacks. The complexity in process will affect performance of the existing system to make insufficient. In this paper, the proposed research work presented a block based feature compression of image in the generation of feature sets. The feature sets are generated based such as vertical, horizontal and are extracted from the image based on range and domain blocks. The extracted features are carried out with encoding and decoding the images. The experimental result shows that block based feature method provides better compression ratio and other parameters when compared with the existing methods such as BTC, Wavelet and DCT.
Fractal Image Compression, Range and Domain Blocks, Encoding and Decoding the Images, BTC - Wavelet and DCT
 N. Ahmed, T. Natarajan and K.R. Rao, “Discrete Cosine Transform”, IEEE Transactions on Computers, Vol. 23, No. 1, pp.90-93, 1974.
 E.J. Delp and O.R. Mitchel, “Image Coding using Block Truncation Coding”, IEEE Transactions on Communications, Vol. 27, pp. 1335-1342, 1979.
 Meftah M. Almrabet, Amer R. Zerek, and AllaouaChaouiAli A. Akash “Image compression using block truncation coding” IJSTA, Vol. 3, No. 2, pp. 1046-1053, 2009.
 Mehdi Salarian, Babak Mohamadinia, and JalilRasekhi, “A Modified No Search Algorithm for Fractal Image Compression”, International Conference on Image Processing, Computer Vision & Pattern Recognition, IPCV 2008, Vol. 2, pp. 14-17, Las Vegas Nevada, 2008.
 Y. Chakrapani1 and K. Soundara Rajan, “Genetic Algorithm Applied To Fractal Image Compression ARPN” Journal of Engineering and Applied Sciences, Vol. 4, No.1, pp 53-58, 2009.
 Sachin Dhawan “A Review of Image Compression and Of Its Algorithms”, IJECT, Vol. 2, No. 1, 2011.
 Sumathi Poobal, and G. Ravindran, “The Performance of Fractal Image Compression on Different Imaging Modalities Using Objective Quality Measures”, International Journal of Engineering Science and Technology, Vol. 2, No.1, pp. 239-246, 2011.
 Anupam Garg “An Improved Algorithm of Fractal Image Compression”, International Journal of Computer Applications, Vol. 34, No. 2, pp. 17-21 2011.
 Chetan Dudhagara and Kishor Atkotiya, “Experimental Study of Fractal Image Compression Algorithm”, International Journal of Computer Applications & Information Technology, Vol. 1, No 2, pp. 18-24, 2012.
 D. Venkatasekhar and P. Aruna, “A Fast Fractal Image Compression Using Huffman Coding”, Asian Journal of Computer Science And Information Technology, Vol. 2, No. 9, pp. 272– 275, 2012.
 Chandan Singh Rawat and Sukadev Meher “A Hybrid Image Compression Scheme Using of Information Technology DCT and Fractal Image Compression”, The International Arab Journal, Vol. 10, No. 6, pp. 553-562, 2013.
 Jianji Wang and Nanning Zheng “A Novel Fractal Image Compression Scheme with Block Classification and Sorting Based on Pearson’s Correlation Coefficient”, IEEE Transactions On Image Processing, Vol. 22, No. 9, pp. 3690-3702, 2013.
 Jie He, and Hui Guo “Super-Sampling Method during Decoding For Fractal Image Compression” Computer Modelling & New Technologies, Vol. 18, No. 12, pp. 501-506, 2014.
 A. Krishnamoorthy “Fast Search Fractal Image Compression Using PSO Based Optimization Technique”, IJCSNS International Journal of Computer Science and Network Security, Vol. 14 No. 6, pp. 122-126, 2014.
 K. Raja Kumari and C. Nalini “Improvement of Image Quality Based On Fractal Image Compression”. Middle-East Journal of Scientific Research, Vol. 20, No. 10, pp. 1213-1217, 2014.
 Preeti Banerjee, Deepak Kumar Xaxa, “Designing and Implementation of Efficient Fuzzy Logic Based Fractal Image Compression Technique”. International Journal of Computer Science and Information Technologies, Vol. 5, No. 3, pp. 3494-3499, 2014.
 S.V. Veenadevi and A.G. Ananth, “Fractal Image Compression of Satellite Color Imageries Using Variable Size of Range Block”, International Journal of Image Processing, Vol. 8, No.1, pp. 1-8, 2014.
 A. R. Nadira Banu Kamal, “Iteration Free Fractal Image Compression for Color Images Using Vector Quantization, Genetic Algorithm and Simulated Annealing” The Online Journal of Science and Technology, Vol. 5, No.1, pp. 39-48, 2015.
 H. Miar Naimi and M. Salarian. “A Fast Fractal Image Compression Algorithm Using Predefined Values for Contrast Scaling.” World congress on Engineering and Computer Science. Vol. 1, No. 4, pp. 1035-1039, 2015.
 K.S. Priyadarshini, and G.S. Sharvani “A Survey on Parallel Computing Of Image Compression Algorithms Jpeg and Fractal Image Compression” Proceedings of the International Conference, “Computational Systems for Health & Sustainability”, pp. 17-18, 2015.
 Thai Nam Son, ThangManh Hoang, Nguyen Tien Dzung,Nguyen Minh Dung, and Pham Ngoc Thang “Fast Implementation of Fractal Image Compression” IJCSNS ,Vol. 2, No. 3, pp. 12-17, 2015.
 M. Salarian, and H. MiarNaimi “Modified Fast Fractal Image Compression Algorithm in Spatial Domain”. Computer Vision and Pattern Recognition Vol. 2, No. 1, pp. 24-27, 2007.