A. Jain, L. Hong, and R. Bolle, "On-line fingerprint verification," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 4, pp. 302--314, 1997.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....using fingerprint, face or voice. Each modality has its advantages and drawbacks (discriminative power, complexity, robustness, etc. Fingerprint verification has been used for a long time. It is based on local properties of ridges and furrows on the fingertip[20] The features, called minutiae [13], are extracted and compared to determine possible matches. The image quality of the fingerprints is very important for minutiae extraction. The matching should also cope with problems like cuts on fingertips. Identification through voice and face is natural and easily accepted by end users. A lot ....

A.K Jain, L. Hong, and R. Bolle. On-line fingerprint verification. IEEE Trans. PAMI, 19(4), 1997.

....of processing related types of imagery. Keywords Fingerprint, enhancement, scale space, a#ne, di#usion, automatic scale selection, image processing. I. Introduction Fingerprint enhancement is a common step in several systems for automatic fingerprint identification [3] 4] 5] 6] [7]. Such systems usually mimic the human procedure for fingerprint identification, consisting of the following processing steps: The image is analyzed in local neighborhoods, to estimate attributes of the ridge patterns, such as ridge width, orientation and curvature, as well as the amount of ....

.... introduce several problems in a later feature detection phase, and hence many mechanisms have been proposed to avoid them [12] 13] 14] Among these approaches, the most flexible one consists of estimating orientations by means of a structure tensor or second moment descriptor [15] 16] 17] [7] and by substituting the contextual filtering step by a special kind of anisotropic di#usion scheme [18] 15] 16] which was first proposed for fingerprint image processing in [16] These ideas have to be further developed in order to design a fully automatic and highly accurate module for ....

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A. Jain, L. Hong, and R. Bolle, "On-line fingerprint verification," IEEE Trans. Pattern Analysis and Machine Intell., vol. 19, no. 4, pp. 302--3013, Apr. 1997.

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A. Jain, L. Hong, and R. Bolle. On-line fingerprint verification. IEEE Trans. Pattern Anal. and Machine Intell., 19(4):302--314, 1997.

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A. Jain, L. Hong, and R. Bolle, "On-line fingerprint verification," IEEE Trans. Pattern Anal. and Machine Intell., Vol. 19, No. 4, pp. 302-314, 1997.

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A. Jain, L. Hong, and R. Bolle. On-line fingerprint verification. IEEE Trans. Pattern Anal. and Machine Intell., 19(4):302--314, 1997.

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Jain, A.K., Hong, L., Bolle, R.: On-line fingerprint verification. IEEE Transactions on PAMI 19 (1997) 302--314

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A. K. Jain, L. Hong, and R. Bolle, "On-line fingerprint verification," IEEE Transactions on PAMI, vol. 19, pp. 302--314, April 1997.

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# A. Jain, L. Hong, and R. Bolle, "On-Line Fingerprint Verification," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 4, pp. 302-314, Apr. 1997.

.... ridge anomalies termed as minutiae points (Figure 1) Typically, the global configuration defined by the ridge structure is used to determine the class [5] 6] of the fingerprint, while the distribution of minutiae points is used to match and establish the similarity between two fingerprints [7][8] Automatic fingerprint identification systems, that match a query print against a large database of prints (which can consist of millions of prints) rely on the pattern of ridges in the query image to narrow their search in the database (fingerprint indexing) and on the minutiae points to ....

....and presents direction for future work. 2 Fingerprint Matching Fingerprint matching techniques can be broadly classified as being minutiaebased or correlation based. Minutiae based techniques attempt to align two sets of minutiae points and determine the total number of matched minutiae [11] 12][7]. Correlation based techniques, on the other hand, compare the global pattern of ridges and furrows to see if the ridges in the two fingerprints 3 align [13] 14] The performance of minutiae based techniques rely on the accurate detection of minutiae points and the use of sophisticated matching ....

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A. K. Jain, L. Hong, R. Bolle, On-line fingerprint verification, IEEE Transactions on PAMI 19 (4) (1997) 302--314.

....impressions. This measure of (dis)similarity is obtained by matching the minutiae point sets of the fingerprint impressions. Our matching algorithm is based on an elastic string matching technique that outputs a distance score indicating the dissimilarity of the minutiae sets being compared [6]. Since our representation of the N fingerprint impressions is in the form of a N x N dissimilarity matrix instead of a N x d pattern matrix (d is the number of features) we use hierarchical clustering [7] In particular, we use an agglomerative complete link clustering algorithm. The output of ....

A. K. Jain, L. Hong, and R. Bolle, "On-line fingerprint verification," IEEE Transactions on PAMI, vol. 19, pp. 302-314, April 1997.

....surface registration problem that can be solved using a modifed ICP algorithm. The initial alignment of fingerprint images I P and I Q is obtained by extracting minutiae points from each individual image, and then comparing the two sets of minutiae points using an elastic point matching algorithm [4]. The comparison proceeds by first selecting a reference minutiae pair (one from each image) and then determining the number of corresponding minutiae pairs using the remaining sets of points in both the images. The reference pair that results in the maximum number of corresponding pairs is ....

....construction: a) First image after segmentation. b) Second Image after segmentation. c) Initial alignment. d) Final alignment. e) Minutiae extracted from mosaicked images. f) Composite minutiae set obtained after augmenting individual minutiae sets. from I R using the algorithm described in [4] (figure 3e) Augmenting Minutiae Sets: If refer to the minutiae sets extracted from I P and I Q , respectively, then a composite minutiae set, is obtained by augmenting . The new (x, y) coordinates of are determined by simply multiplying the old coordinates (Figure 3f) The ....

Anil K. Jain, Lin Hong, and Ruud Bolle, "On-line fingerprint verification," IEEE Transactions on PAMI, vol. 19, no. 4, pp. 302--314, Apr 1997.

.... K images) for the 4 filtered images in figure 4. 3. Hybrid Fingerprint Matcher The hybrid fingerprint matcher proposed here utilizes two distinct sets of fingerprint information: minutiae features, and ridge feature maps. Minutiae information is obtained using the technique described in [4]. When a query image is presented, the matching proceeds as follows: i) the query and template minutiae features are matched to generate a minutiae matching score and an affine transformation that aligns the query and template fingerprints; ii) the query image is filtered using Gabor filters; ....

....in the two fingerprint images. This is done by determining the affine transformation parameters, 0 4 , that would align the query image with the template. The transformation parameters are computed by matching the two sets of minutiae points using an elastic point matching algorithm [4]. Instead of rotating the query image by and then filtering it, the Gabor filters are appropriately rotated and the modified Gabor filter bank is applied to the query image. The resulting filtered images are then rotated by and translated by 0 4 . This reduces the artifacts ....

A. K. Jain, L. Hong, and R. Bolle. On-line fingerprint verification. IEEE Transactions on PAMI, 19(4):302--314, Apr 1997.

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A. K. Jain and Lin Hong, On-line Fingerprint Verification, to appear in Proc. 13th ICPR, Vienna, Austria, 1996.

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A. Jain, L. Hong, and R. Bolle, On-line Fingerprint Verification, IEEE Trans. on PAMI, Vol. 19, No. 4, 1997.

....their fingerprints into the system database. When the fingerprint images and the user name of a person to be enrolled are fed to the enrollment module, a minutiae extraction algorithm is first applied to the fingerprint images and the minutiae patterns are extracted. A quality checking algorithm [33] is used to ensure that the records in the system database only consist of fingerprints of good quality, in which a significant number (default value is 25) of genuine minutiae may be detected. This is important, because there is no point in using a minutiae pattern with only a very limited number ....

....point in using a minutiae pattern with only a very limited number of genuine minutiae as a template to make an authentication. If a fingerprint image is of poor quality, it is enhanced to improve the clarity of ridge valley structures and mask out all the regions that cannot be reliably recovered [33]. The enhanced fingerprint image is fed to the minutiae extractor again. Because the current quality checking algorithm is very slow [33] it is only used in the enrollment module. The task of authentication module is to authenticate the identity of the person who intends to access the system. The ....

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A. Jain and L. Hong, On-line Fingerprint Verification, Proc. 13th ICPR, Vienna, pp. 596-600, 1996.

....ridges and furrows are permanent and do not change with time [13] The uniqueness of a fingerprint is exclusively determined by the local ridge characteristics and their relationships. Fingerprint matching generally depends on the comparison of local ridge characteristics and their relationships [13, 11, 14, 16, 23]. A total of one hundred and fifty different local ridge characteristics, called minute details, have been identified [13] These local ridge characteristics are not evenly distributed. Most of them depend heavily on the impression conditions and quality of fingerprints and are rarely observed in ....

....map (d) extracted minutiae Figure 7. Results of our minutiae extraction algorithm on a fingerprint image (512 Theta 512) captured with an optical scanner. y coordinates, and its direction, whose definitions are also shown in Figure 6(c) Fingerprint verification consists of two main stages [11, 13]: i) minutiae extraction and (ii) minutiae matching. Due to a number of factors such as aberrant formations of epdiermal ridges of fingerprints, postnatal marks, occupational marks, problems with acquisition devices, etc. acquired fingerprint images may not always have well defined ridge ....

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A. Jain, L. Hong, and R. Bolle, On-line Fingerprint Verification, IEEE Trans. PAMI, Vol. 19, No. 4, 1997.

....on either (i) binary ridge images or (ii) graylevel images. A binary ridge image is an image where all the ridge pixels are assigned a value 1 and non ridge pixels are assigned a value 0. The binary image can be obtained by applying a ridge extraction algorithm on a gray level fingerprint image [6]. Since ridges and furrows in a fingerprint image alternate and run parallel to each other in a local neighborhood, a number of simple heuristics can be used to differentiate the spurious ridge configurations from the true ridge configurations in a binary ridge image [5] However, after applying a ....

....minutiae. 3. 2 Evaluation Using Verification Performance The performance of the enhancement algorithm was also assessed on the first volume of the MSU fingerprint database (700 live scan images; 10 per individual) using the verification accuracy of an online fingerprint verification system [6]. We demonstrated that incorporating the enhancement algorithm in the fingerprint verification system improves the system performance. In the first test, the fingerprint enhancement algorithm was not applied. Each fingerprint image in the data set was directly matched against the other fingerprint ....

A. Jain, L. Hong, and R. Bolle. On-line fingerprint verification. IEEE Trans. Pattern Anal. and Machine Intell., 19(4):302--314, 1997.

....or a ridge pattern matching of input fingerprint images. Because the general point matching problem is essentially intractable, features associated with each point and inter point distances are widely used in the point pattern matching algorithms to reduce the exponential number of search paths [4, 1, 10, 8]. However, these algorithms are inherently slow and are unsuitable for an automatic identity authentication system. In our system, an alignment based matching algorithm is implemented, which decomposes the minutia matching into two stages: i) alignment stage, where transformations such as ....

A. Jain and L. Hong, On-line Fingerprint Verification, Proc. 13th ICPR, Vienna, pp. 596-600, 1996.

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A. Jain, L. Hong, and R. Bolle, "On-line fingerprint verification," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 4, pp. 302--314, 1997.

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A. K. Jain, L. Hong, and R. Bolle, "On-line Fingerprint Verification," IEEE Trans. PAMI, vol. 19, no. 4, pp. 302--314, 1997.

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A. K. Jain, L. Hong, and R. Bolle, "On-line fingerprint verification," IEEE Trans. Pattern Anal. Machine Intell., vol. 19, no. 4, pp. 302--314, 1997.

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A. K. Jain, L. Hong, and R. Bolle, "On-line fingerprint verification," IEEE Trans. PAMI, vol. 19, no. 4, pp. 302--314, 1997.

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A. K. Jain, L. Hong and R. Bolle, "On-line fingerprint verification", IEEE Trans. Pattern Analysis Machine Intelligent, Vol. 19, No. 4, pp.302-314, 1997.

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A. K. Jain, L. Hong, and R. M. Bolle, "On-line fingerprint verification," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 4, pp. 302--314, 1997.

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Jain, A., Hong, L., Bolle, R.: On-line fingerprint verification. IEEE-PAMI 19 (1997) 302--314

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A.K. Jain, L. Hong, and R. Bolle, "On-line Fingerprint Verification", IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(4) 302-314, 1997.

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Jain,A., Hong,L. and Bolle,R.: On-Line Fingerprint Verification. IEEE-PAMI, Vol.19, No.4, pp. 302-314, Apr. 1997.

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A. Jain and L. Hong, "On-line fingerprint verification", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.19 (4), pp. 302-314, 1997.

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A.K. Jain, L. Hong, and R. Bolle, "On-line fingerprint verification, " IEEE Trans. PAMI, vol. 19, no. 4, pp. 302--314, Apr. 1997.

No context found.

A. Jain and L. Hong, "On-line Fingerprint Verification", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.19 (4), pp. 302-314, 1997.

No context found.

A. K. Jain, L. Hong, and R. Bolle, "On-line Fingerprint Verification," IEEE Trans. Pattern Anal. and Machine Intell., Vol. 19, No. 4, pp. 302-314, 1997.

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