2019
DOI: 10.1016/j.imavis.2019.02.006
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Two-stage quality adaptive fingerprint image enhancement using Fuzzy C-means clustering based fingerprint quality analysis

Abstract: Fingerprint recognition techniques are immensely dependent on quality of the fingerprint images. To improve the performance of recognition algorithm for poor quality images an efficient enhancement algorithm should be designed. Performance improvement of recognition algorithm will be more if enhancement process is adaptive to the fingerprint quality (wet, dry or normal). In this paper, a quality adaptive fingerprint enhancement algorithm is proposed. The proposed fingerprint quality assessment algorithm cluste… Show more

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Cited by 30 publications
(13 citation statements)
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“…To demonstrate the efficiency of the proposed method, we compared the results obtained using the proposed method with those obtained using related methods, including histogram equalization (HE) [34], Sharma and Dey [11], and the method of Wang et al [19]. Experiments were performed using multiple fingerprint databases, including FVC 2002 and NIST-4.…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…To demonstrate the efficiency of the proposed method, we compared the results obtained using the proposed method with those obtained using related methods, including histogram equalization (HE) [34], Sharma and Dey [11], and the method of Wang et al [19]. Experiments were performed using multiple fingerprint databases, including FVC 2002 and NIST-4.…”
Section: Resultsmentioning
confidence: 99%
“…Fig. 7 illustrates some images from NIST-4 and enhancement images obtained after using HE [34], Sharma and Dey [11], Wang et al [19], and the proposed method. The results show that the enhanced fingerprint images by the proposed algorithm have better quality in comparison with the other method.…”
Section: Resultsmentioning
confidence: 99%
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“…Since it's hard for online AFIS to obtain the number of clusters, those methods have difficulty in deploying their framework in practice. Furthermore, various previous block-based works neglect the significance of pixel value [20], [21]. Therefore, how to reduce the probability of identification mismatch and adaptly improve the efficiency of the fingerprint segmentation remains an open problem.…”
Section: Related Workmentioning
confidence: 99%
“…To recognize a face, following approach (see fig.1) is used, because the face is completely a complex multidimensional structure. So, there is a need to compute better recognition techniques with enhanced input data [13]. Therefore, in this research, the complexity problem is overcome by using pre-processing, feature extraction, and optimization technique with classifiers.…”
Section: E Improved Face Recognition System (Ifrs)mentioning
confidence: 99%