chapter 7 conclusion and scope for future...

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CHAPTER 7

CONCLUSION AND SCOPE FOR FUTURE WORK

7.1 CONCLUSION

Efficient image compression techniques are becoming very vital in

areas like pattern recognition, image processing, system modeling, data

mining, etc. Compression techniques have become the most

concentrated area in the field of computer. Image compression is a

technique of efficiently coding digital image to reduce the number of bits

required in representing an image. The present research work proposes

three novel techniques using vector quantization for effective image

compression. Code book generation using vector quantization is the

principal step in this research work. The present research work uses

effective clustering technique for the code book generation. Effective

clustering techniques such as Modified K-Means, Modified Fuzzy

Possibilistic C-Means with Repulsion, Modified Fuzzy Possibilistic C-

Means with repulsion and Weighted Mahalanobis Distance are used in

this research for better compression results.

The performance of the proposed approaches is evaluated on the

basis of parametric standards like SSE, Entropy, Execution Time and

PSNR value. The performance is compared to the standard approaches

like K-Means, LBG and MFPCM. It is clearly observed from the

experimental results that the proposed approaches outperform the

standard approaches like K-Means, MFPCM and LBG. The performance

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156

is evaluated on three standard images like Lena, Cameraman and

Peppers.

Among the proposed approaches, the proposed Modified Fuzzy

Possibilistic C-Means with repulsion and Weighted Mahalanobis

Distance approach used for code generation has the least SSE when

compared to the other proposed approaches. Similarly, the entropy

value, Execution time and Coding of VQ indices are also very much less

when compared to the other approaches reviewed in the literature.

PSNR value of the proposed Modified Fuzzy Possibilistic C-

Means with repulsion and Weighted Mahalanobis Distance approach is

very high when compared to the other proposed approaches.

Thus, the proposed image compression technique which uses

Modified Fuzzy Possibilistic C-Means with repulsion and Weighted

Mahalanobis Distance for code book generation outperforms the other

proposed approaches in terms of all the parameters taken into

consideration.

7.2 SCOPE FOR FUTURE WORK

The present research mainly focused on the effective image

compression techniques using vector quantization approaches. Code

book generation is the main technique that has been taken up for

research in this thesis. The present research has used three effective

code book generation approaches for efficient image compression

techniques. Code book generation is based on the clustering


157

approaches such as Modified K-Means, Modified Fuzzy Possibilistic C-

Means with repulsion, Modified Fuzzy Possibilistic C-Means with

repulsion and Weighted Mahalanobis Distance. It is observed from the

experimental results that the proposed approach provides better results

when compared to the standard code book generation techniques.

The future enhancement of this research work would be to

increase the PSNR value with less computation time. Some of the future

extensions of this research are listed below:

Recent clustering techniques based on the Swarm Intelligence (AI)

may be used for code book generation which may increase the

overall performance of the system.

The techniques based on the evolutionary algorithms (Ants, Bees

etc.,) which may be used to provide better optimized results, which

make use of genetic algorithm.

Effective Neuro-fuzzy techniques can be incorporated with the

vector quantization technique for better overall performance.


158

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LIST OF PUBLICATIONS

CONFERENCES

1. Distributed Data Warehouse Construction and Accessing

Tool, UGC Sponsored National Conference on Computer

Science and Informatics, St.Joseph College, Trichy, 18th & 19th

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3. Multicast Group Based Computation Time Reduction Scheme

for Grid Environment, UGC Sponsored National Conference on

Web Services, PSG College of Arts & Science College,

Coimbatore, 20th and 21st March 2007.

4. Adaptive Web Search and Navigation Using PWNE , UGC

Sponsored National Conference on Data Warehousing and

Data Mining, Gobi Arts & Science College, Gobichettipalayam,

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No. 8, Nov 2010.

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Mahalanobis Distance International Journal of Electrical,

Electronics and Computer Systems, Vol.3,Issue 2, Aug 2011.

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