@MASTERSTHESIS\{IMM2013-06685,
    author       = "J. Wang",
    title        = "Finger Image Quality Based on Singular Point Localization",
    year         = "2013",
    school       = "Technical University of Denmark, Department of Applied Mathematics and Computer Science",
    address      = "Matematiktorvet, Building 303B, {DK-}2800 Kgs. Lyngby, Denmark, compute@compute.dtu.dk",
    type         = "",
    note         = "{DTU} supervisor: Rasmus Larsen, rlar@dtu.dk, {DTU} Compute",
    url          = "http://www.compute.dtu.dk/English.aspx",
    abstract     = "Finger image quality assessment is a crucial task in the fingerprint-based biometric systems, and plenty of publications state that singular points have the profound influence on the biometric performance. The aim of the thesis is to analyse whether the singular points are significant and what is the degree of importance on the biometric performance.
Existing approaches of orientation field estimation and singular point localization are discussed in this work, and the most accurate and robust of them are applied. Five pattern-based filters are proposed to reduce the detected spurious singular points. One segmentation algorithm is proposed using morphological image processing.
Seven singular point localization-based global Quality Measurement Algorithms are proposed to systematically analyse the effect of singular points on the biometric performance by measuring the finger sample displacement and rotation. Experimental results establish the property of singular points does have influence on biometric performance although not better than the analysis of fine level characteristics. Four local Quality Measurement Algorithms are proposed to give the quality score by analysing the coherence of the ridgeline. Acceptable results are achieved with excellent execution time.
Additionally all the proposed Quality Measurement Algorithms can be potentially incorporated in the {ISO}/{IEC} standards or in {NIST} Finger Image Quality 2.0."
}