Efficient Quantization Method for Biometric Fingerprint Image Compression

B. S. Emmanuel *

Department of Electrical and Computer Engineering, Ahmadu Bello University, Zaria, Nigeria.

M. B. Mu’azu

Department of Electrical and Computer Engineering, Ahmadu Bello University, Zaria, Nigeria.

S. M. Sani

Department of Electrical and Computer Engineering, Ahmadu Bello University, Zaria, Nigeria.

S. Garba

Department of Electrical and Computer Engineering, Ahmadu Bello University, Zaria, Nigeria.

*Author to whom correspondence should be addressed.


Abstract

The choice of quantization method and the requirement to achieve a trade-off between compressed image quality and degradation are very crucial in the overall performance of a lossy image compression algorithm. In this paper, uniform and non-uniform scalar quantization schemes of biometric fingerprint image were studied. Comparative analyses of non-uniform quantization methods were also conducted and these include dither-based quantization and the Lloyd-Max quantization methods.  The quality of the quantized output fingerprint image was determined in terms of Signal-to-Quantization Noise Ratio (SQNR). The degree of distortion or quantization error was determined in terms of the Mean Square Quantization Error (MSQE). The non-uniform quantization method performed better than the uniform quantization method in terms of the SQNR and MSQE values. It was also found out that, the performance of dither-based non-uniform quantization on biometric fingerprint image is not as efficient as the Lloyd-Max approach when the number of bits used in the quantization process increased. The results showed that the higher the number of bits used in the quantization process the higher the quality and the less the distortion in the resulting images.

Keywords: Biometric fingerprint, image compression, quantization, dither.


How to Cite

Emmanuel, B. S., M. B. Mu’azu, S. M. Sani, and S. Garba. 2015. “Efficient Quantization Method for Biometric Fingerprint Image Compression”. Journal of Advances in Mathematics and Computer Science 10 (3):1-19. https://doi.org/10.9734/BJMCS/2015/18438.

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