B. G. Sherlock, D. M. Monro, and K. Millard. Fingerprint enhancement by directional fourier filtering. IEEE Proceedings in Visual Image Signal Processing, 141(2):87--94, April 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....extraction. The binarization process requires image enhancement, then a threshold based decision distinguishes ridges and valleys. In [2] O Gorman and Nickerson present an enhancement technique based on the convolution of the image with a filter oriented according to the directional image. In [3], Sherlock, Monro and Millard propose a directional filtering process in the Fourier domain. The more precise approach proposed in [4] takes the local frequency into account using a local Fourier transform. The method is efficient but time consuming. To speed up the process, the authors have to ....

- B.G Sherlock, D.M Monro and K. Millard, "Fingerprint Enhancement by Directional Fourier Filtering", Proc. Conf. Vision, Image and Signal Processing, pp. 87-94, 1994.

....This formulation substantially improves the matching time in a one to many matching scheme. 3. 1 Fingerprint Enhancement Enhancement is the process by which the clarity of the ridge and furrow structures in the fingerprint images is improved to facilitate the feature extraction process [18] [19]. Fingerprint enhancement helps in reducing the noise content in the fingerprint image. Enhancement, however, can also introduce false ridges, resulting in spurious or missing minutiae points. Since the ridge feature map representation proposed here relies on the dominant ridge directions in each ....

D. Sherlock, D. M. Monro, K. Millard, Fingerprint enhancement by directional fourier filtering, IEE Proceedings on Vision, Image and Signal Processing 141 (2) (1994) 87--94.

....the Ridge Feature Map The 240 240 input fingerprint image, I , is convolved with the 8 Gabor filters, G . Since the input image may be noisy, it is first enhanced before applying the filters. Enhancement improves the clarity of the ridge and furrow structure in the fingerprint image [10]. We use the technique described in [9] to enhance the fingerprint image (Figure 2(b) A segmentation algorithm is also applied on the input image to identify the foreground and background regions. The foreground corresponds to those regions in the image that have ridges and furrows, while the ....

D. Sherlock, D. M. Monro, and K. Millard, "Fingerprint enhancement by directional fourier filtering," IEE Proceedings on Vision, Image and Signal Processing, vol. 141, no. 2, pp. 87--94, 1994.

....images in recoverable regions and to mask out the unrecoverable regions. Another very important aspect concerning a fingerprint enhancement algorithm is that it should not result in any spurious ridge valley structures. A number of techniques have been proposed to enhance fingerprint images [1, 4, 5, 7, 11, 16, 17]. These techniques take advantage of the information about the local ridge valley structures and are capable of adaptively improving the quality of input fingerprint images [1, 4, 5, 7, 17] However, all of these techniques make an assumption that the local ridge valley orientations can be ....

....ridge valley structures. A number of techniques have been proposed to enhance fingerprint images [1, 4, 5, 7, 11, 16, 17] These techniques take advantage of the information about the local ridge valley structures and are capable of adaptively improving the quality of input fingerprint images [1, 4, 5, 7, 17]. However, all of these techniques make an assumption that the local ridge valley orientations can be reliably estimated from input fingerprint images. In practice, this assumption is not true for fingerprint images of poor quality. Figure 3 shows some examples of estimated orientation field of ....

D. B. G. Sherlock, D. M. Monro, and K. Millard, Fingerprint Enhancement by Directional Fourier Filtering, IEE Proc. Vis. Image Signal Processing, Vol. 141, No. 2, pp. 87-94, 1994.

....Thus, a substantial amount of research reported in the literature on fingerprint identification is devoted to image enhancement techniques. We describe briefly our feature extraction method presented in [36] While our approach uses many of the well known ideas proposed in the earlier studies [39, 27, 19, 49], the ridge flow orientations form the basis for adapting parameters in all the stages of our feature extraction algorithm. We view a fingerprint image as a flow pattern with a definite texture. To accurately determine the local orientation field, the input image is divided into equal sized blocks ....

....November 1995. 37] I. Rigoutsos and R. Hummel. Massively parallel model matching. IEEE Computer, 25(2) 33 42, February 1992. 38] N. Roussopolous, C. Faloutsos, and T. Sellis. An efficient pictorial database system for PSQL. IEEE Trans. on Software Engineering, 14(5) 639 650, May 1988. [39] B. G. Sherlock, D. M. Monro, and K. Millard. Fingerprint enhancement by directional Fourier filtering. IEE Proc. Vis. Image Signal Processing, 141(2) 87 94, April 1994. 40] S. W. Smoliar and H. Zhang. Content based video indexing retrieval. IEEE Multimedia, Summer:62 72, 1994. 41] V. S. ....

B. G. Sherlock, D. M. Monro, and K. Millard. Fingerprint enhancement by directional Fourier filtering. IEE Proc. Vis. Image Signal Processing, 141(2):87--94, April 1994.

....In a gray level fingerprint image, ridges and furrows in a local neighborhood form a sinusoidal shaped plane wave which has a well defined frequency and orientation. A number of techniques that take advantage of this information have been proposed to enhance graylevel fingerprint images [2, 15, 8, 18, 19]. However, they usually assume that the local ridge orientations can be reliably estimated. In practice, this assumption is not valid for fingerprint images of poor quality, which greatly restricts the applicability of these techniques. Hong etal: 4] proposed a decomposition method to estimate ....

D. Sherlock, D. M. Monro, and K. Millard. Fingerprint enhancement by directional fourier filtering. IEE Proc. Vis. Image Signal Processing, 141(2):87--94, 1994.

No context found.

B. G. Sherlock, D. M. Monro, and K. Millard. Fingerprint enhancement by directional fourier filtering. IEEE Proceedings in Visual Image Signal Processing, 141(2):87--94, April 1994.

No context found.

Sherlock,D., Monro,D.M. and Millard,K.: Fingerprint Enhancement by Directional Fourier Filtering. IEEE Proceedings on Visual Imaging Signal Processing, 141: 87-94, 1994

No context found.

B. G. Sherlock, D. M. Monro, and K. Millard, "Fingerprint Enhancement By Directional Fourier Filtering," IEE Proc. - Vision, Image, Signal Proc., vol. 141, no. 2, pp. 87-94, 1994.

No context found.

D. B. G. Sherlock, D. M. Monro, and K. Millard, "Fingerprint Enhancement by Directional Fourier Filtering," Proc. Inst. Elect. Eng. Visual Image Signal Processing, Vol. 141, No. 2, pp. 87-94, 1994.

No context found.

D. B. G. Sherlock, D. M. Monro and K. Millard, Fingerprint Enhancement by Directional Fourier Filtering, IEE Proc. Vis. Image Signal Processing, Vol. 141, No. 2, pp. 87-94, 1994.

No context found.

D. B. G. Sherlock, D. M. Monro and K. Millard, Fingerprint Enhancement by Directional Fourier Filtering, IEE Proc. Vis. Image Signal Processing, Vol. 141, No. 2, pp. 87-94, 1994.

No context found.

B. G. Sherlock, D. M. Monro, and K. Millard. Fingerprint enhancement by directional Fourier filtering. IEE Proc. Vis. Image Signal Processing, 141(2):87--94, April 1994.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC