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  • 1.
    Bartunek, Josef Strom
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Nilsson, Mikael
    Sällberg, Benny
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Claesson, Ingvar
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Adaptive Fingerprint Image Enhancement With Emphasis on Preprocessing of Data2013In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 22, no 2, p. 644-656Article in journal (Refereed)
    Abstract [en]

    This article proposes several improvements to an adaptive fingerprint enhancement method that is based on contextual filtering. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. Five processing blocks comprise the adaptive fingerprint enhancement method, where four of these blocks are updated in our proposed system. Hence, the proposed overall system is novel. The four updated processing blocks are: 1) preprocessing; 2) global analysis; 3) local analysis; and 4) matched filtering. In the preprocessing and local analysis blocks, a nonlinear dynamic range adjustment method is used. In the global analysis and matched filtering blocks, different forms of order statistical filters are applied. These processing blocks yield an improved and new adaptive fingerprint image processing method. The performance of the updated processing blocks is presented in the evaluation part of this paper. The algorithm is evaluated toward the NIST developed NBIS software for fingerprint recognition on FVC databases.

  • 2. Engelke, Ulrich
    et al.
    Liu, Hantao
    Wang, Junle
    Le Callet, Patrick
    Heynderickx, Ingrid E J
    Zepernick, Hans-Jürgen
    Blekinge Institute of Technology, School of Computing.
    Maeder, Anthony J.
    Comparative Study of Fixation Density Maps2013In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 22, no 3, p. 1121-1133Article in journal (Refereed)
    Abstract [en]

    Fixation density maps (FDM) created from eye tracking experiments are widely used in image processing applications. The FDM are assumed to be reliable ground truths of human visual attention and as such, one expects a high similarity between FDM created in different laboratories. So far, no studies have analyzed the degree of similarity between FDM from independent laboratories and the related impact on the applications. In this paper, we perform a thorough comparison of FDM from three independently conducted eye tracking experiments. We focus on the effect of presentation time and image content and evaluate the impact of the FDM differences on three applications: visual saliency modeling, image quality assessment, and image retargeting. It is shown that the FDM are very similar and that their impact on the applications is low. The individual experiment comparisons, however, are found to be significantly different, showing that inter-laboratory differences strongly depend on the experimental conditions of the laboratories. The FDM are publicly available to the research community.

  • 3. Sattar, Farook
    et al.
    Floreby, Lars
    Salomonsson, Göran
    Lövström, Benny
    Blekinge Institute of Technology, Department of Signal Processing.
    Image Enhancement based on a Nonlinear Multiscale Method1997In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 6, no 6, p. 888-895Article in journal (Refereed)
    Abstract [en]

    An image enhancement method that reduces speckle noise and preserves edges is introduced. The method is based on a new nonlinear multiscale reconstruction scheme that is obtained by successively combining each coarser scale image with the corresponding modified interscale image. Simulation results are included to demonstrate the performance of the proposed method.

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