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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.
    Khan, Imran
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Muthusamy, Dineshkumar
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Ahmad, Waqas
    Sällberg, Benny
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Nilsson, Kristian
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Zackrisson, Johan
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Gustavsson, Ingvar
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Håkansson, Lars
    Performing active noise control and acoustic experiments remotely2012In: International Journal of Online Engineering, ISSN 1868-1646, E-ISSN 1861-2121, Vol. 8, no special issue 2, p. 65-74Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel and advanced remotely controlled laboratory for conducting Active Noise Control (ANC), acoustic and Digital Signal Processing (DSP) experiments. The laboratory facility, recently developed by Blekinge Institute of Technology (BTH) Sweden, supports remote learning through internet covering beginners level such as simple experimental measurements to advanced users and even researchers such as algorithm development and their performance evaluation on DSP. The required software development for ANC algorithms and equipment control are carried out anywhere in the world remotely from an internet-connected client PC using a standard web browser. The paper describes in detail how ANC, acoustic and DSP experiments can be performed remotely The necessary steps involved in an ANC experiment such as validity of ANC, forward path estimation and active control applied to a broad band random noise [0-200Hz] in a ventilation duct will be described in detail. The limitations and challenges such as the forward path and nonlinearities pertinent to the remote laboratory setup will be described for the guidance of the user. Based on the acoustic properties of the ventilation duct some of the possible acoustic experiments such as mode shapes analysis and standing waves analysis etc. will also be discussed in the paper.

  • 3.
    Khan, Muhammad Gufran
    et al.
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Sällberg, Benny
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Nordberg, Jörgen
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Tufvesson, Fredrik
    Claesson, Ingvar
    Blekinge Institute of Technology, School of Engineering, Department of Electrical Engineering.
    Non-Coherent Fourth-Order Detector for Impulse Radio Ultra Wideband Systems: Empirical Evaluation Using Channel Measurements2013In: Wireless personal communications, ISSN 0929-6212, E-ISSN 1572-834X, Vol. 68, no 1, p. 27-46Article in journal (Refereed)
    Abstract [en]

    Low-complex and low-power non-coherent energy detectors (EDs) are interesting for low data rate impulse radio (IR) ultra wideband (UWB) systems, but suffer from a loss in performance compared to coherent receivers. The performance of an ED also strongly depends on the integration interval (window size) of the integrator and the window position. This paper presents a non-coherent fourth-order detector (FD) which can discriminate between Gaussian noise signals and non-Gaussian IR-UWB signals by directly estimating the fourth-order moment of the received signal. The performance of the detectors is evaluated using realistic channels measured in a corridor, an office and a laboratory environment. The results show that bit-error-rate (BER) performance of the proposed FD receiver is slightly better than the ED in low signal-to-noise ratio (SNR) region and its performance improves as the SNR increases. In addition, BER of the FD receiver is less sensitive to overestimation of the integration interval making it relatively robust to variations of the channel delay spread. Finally, a criteria for the selection of integration time of the proposed detector is suggested.

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