Performance Analysis on the Assessment of Fingerprint Image Based on Blur Measurement

Processing the fingerprint image captured from the mobile phone camera is problematic. The addressed problem is such as degree of freedom, blurry, noisy and weak ridges-valleys images. In this paper, problem of blur assessment on fingerprint image is the main consent. In this regards, dataset of fingerprint image is collected from several subjects and different environment to obtain a clear and blur fingerprint image. The ground truth for this dataset is assigned by human vision. According to literature, the suitable blur evaluation is based on no-reference strategy. Hence, this paper modified existing no-reference blur assessment so it is suitable for fingerprint image. The proposed method achieved promising result and able to detect blur and clear fingerprint image.

[1]  Xuezheng Liu,et al.  Bayesian motion blur identification using blur priori , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[2]  Sheila S. Hemami,et al.  A metric for continuous quality evaluation of compressed video with severe distortions , 2004, Signal Process. Image Commun..

[3]  A. Murat Tekalp,et al.  Maximum likelihood parametric blur identification based on a continuous spatial domain model , 1992, IEEE Trans. Image Process..

[4]  Sheila S. Hemami,et al.  A scalable wavelet-based video distortion metric and applications , 2006, IEEE Transactions on Circuits and Systems for Video Technology.

[5]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[6]  Jorge E. Caviedes,et al.  No-reference sharpness metric based on local edge kurtosis , 2002, Proceedings. International Conference on Image Processing.

[7]  Zhou Wang,et al.  Quality-aware images , 2006, IEEE Transactions on Image Processing.

[8]  Joonki Paik,et al.  Simultaneous out-of-focus blur estimation and restoration for digital auto-focusing system , 1998 .

[9]  Alan C. Bovik,et al.  41 OBJECTIVE VIDEO QUALITY ASSESSMENT , 2003 .

[10]  A. Bovik,et al.  OBJECTIVE VIDEO QUALITY ASSESSMENT , 2003 .

[11]  Michael W. Marcellin,et al.  Blur identification from vector quantizer encoder distortion , 1998, IEEE Trans. Image Process..

[12]  Stefan Winkler,et al.  Perceptual blur and ringing metrics: application to JPEG2000 , 2004, Signal Process. Image Commun..

[13]  Aggelos K. Katsaggelos,et al.  A VQ-based blind image restoration algorithm , 2003, IEEE Trans. Image Process..

[14]  Weisi Lin,et al.  A no-reference quality metric for measuring image blur , 2003, Seventh International Symposium on Signal Processing and Its Applications, 2003. Proceedings..

[15]  A. Murat Tekalp,et al.  Identification of image and blur parameters for the restoration of noncausal blurs , 1986, IEEE Trans. Acoust. Speech Signal Process..

[16]  Bülent Sankur,et al.  Statistical evaluation of image quality measures , 2002, J. Electronic Imaging.

[17]  Lina J. Karam,et al.  No-reference objective wavelet based noise immune image sharpness metric , 2005, IEEE International Conference on Image Processing 2005.

[18]  Ming-Chao Chiang,et al.  Local blur estimation and super-resolution , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[19]  Bülent Sankur,et al.  Statistical analysis of image quality measures , 2000, 2000 10th European Signal Processing Conference.

[20]  M. S. Khalil,et al.  Singular points detection using fingerprint orientation field reliability , 2010 .

[21]  Mostafa Kaveh,et al.  Blind image restoration by anisotropic regularization , 1999, IEEE Trans. Image Process..

[22]  Alan C. Bovik,et al.  Image information and visual quality , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[23]  Moon Gi Kang,et al.  An Algorithm To Extract Camera-shaking Degree And Noise Variance In The Peak-trace Domain. , 1998, International 1998 Conference on Consumer Electronics.

[24]  Patricia Ladret,et al.  The blur effect: perception and estimation with a new no-reference perceptual blur metric , 2007, Electronic Imaging.

[25]  J. Paik,et al.  Out-of-focus blur estimation and restoration for digital auto-focusing system , 1998 .

[26]  Wei-Ying Ma,et al.  Blur determination in the compressed domain using DCT information , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[27]  Lina J. Karam,et al.  A No-Reference Objective Image Sharpness Metric Based on the Notion of Just Noticeable Blur (JNB) , 2009, IEEE Transactions on Image Processing.

[28]  Giorgio Bonmassar,et al.  Real-time restoration of images degraded by uniform motion blur in foveal active vision systems , 1999, IEEE Trans. Image Process..

[29]  Muhammad Khurram Khan,et al.  Protecting Biometric Data for Personal Identification , 2004, SINOBIOMETRICS.

[30]  Tony F. Chan,et al.  Total variation blind deconvolution , 1998, IEEE Trans. Image Process..

[31]  Alexandre G. Ciancio,et al.  No-Reference Blur Assessment of Digital Pictures Based on Multifeature Classifiers , 2011, IEEE Transactions on Image Processing.

[32]  Ben Liang,et al.  Blind image deconvolution using a robust GCD approach , 1999, IEEE Trans. Image Process..

[33]  Stefan Winkler,et al.  A no-reference perceptual blur metric , 2002, Proceedings. International Conference on Image Processing.

[34]  Gerard de Haan,et al.  Low Cost Robust Blur Estimator , 2006, 2006 International Conference on Image Processing.

[35]  Jean-Bernard Martens,et al.  Multidimensional modeling of image quality , 2002, Proc. IEEE.

[36]  M. Cannon Blind deconvolution of spatially invariant image blurs with phase , 1976 .