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Contrast Fingerprint Enhancement Based on Histogram Equalization Followed By Bit Reduction of Vector Quantization


Muna F. Hanoon


Vol. 11  No. 5  pp. 116-123


Fingerprint minutiae are presently used in fingerprint image enhancement. The extraction of fingerprint minutiae is heavily affected by the quality of fingerprint images. This leads to the incorporation of fingerprint enhancement module in fingerprint recognition systems to make the system robust with respect to the quality of input fingerprint images. Histogram equalization (HE) is widely used for contrast enhancement. However, it leads to change the brightness of an image. Preserving the input brightness of the image is required to avoid annoying artifacts in an output image. The goal of image enhancement technique is to improve the characteristics or quality of an image such that the resulting image is better than the original image which is the objective in this paper. A low bit rate image coding scheme based on vector quantization is proposed. The block prediction coding techniques are employed to cut down the required bit rate of vector quantization. In block prediction coding neighboring encoded blocks are taken to compress the current block. So we investigated the performance of four steps procedure for fingerprint compression and enhancement using contrast limited adaptive histogram equalization with clip limit (CLAHE), Wiener filtering, image binarization, thinning and Vector Quantization (VQ). In conclusion, the paper is shown some improvement in the minutiae detection process in terms of efficiency and time required. Input here the part of summary.


image enhancement, vector quantization, histogram equalization, business intelligence and fingerprint