Mlambo, CSMathekga, Mmamolatelo ENelwamondo, Fulufhelo V2015-08-192015-08-192014-10Mlambo, C.S, Mathekga, M.E and Nelwamondo, F.V. 2014. A study of Hough Transform-based fingerprint alignment algorithms. International Journal of Computer Applications, vol. 103(8), pp 1-80975 8887http://research.ijcaonline.org/volume103/number8/pxc3899158.pdfhttp://hdl.handle.net/10204/8052Copyright: 2015 Foundation of Computer Science. This is an Open Access journal. This journal authorizes the publication of the information herewith contained. Published in International Journal of Computer Applications, vol. 103(8), pp 1-8This paper classifies existing Hough Transform fingerprint alignment algorithms and compares their performance to determine the one that gives optimal alignment results (translation and rotation). The classification is performed by considering the implementation of each algorithm. The comparison is performed by considering the alignment results computed using each group of algorithms when varying number of minutiae points, rotation angle, and translation. In addition, the memory usage, computing time and accuracy are taken into consideration. The experiments were performed on a small database where fingerprints were captured in different orientations and locations and on the public database FVC2004. Three classes of Hough Transform-Based approaches were classified as the Local Match Based Alignment(LMBA), Discretized Rotation Based Alignment(DRBA) and Matching Pair Based Alignment (MPBA). The results revealed good accuracy on all three approaches, however, the computing time and memory usage affected the performance of each approach. The LMBA approach perform better than the DRBA and the MPBA approaches on minutiae points set with larger rotation and small number of points. The DRBA approach was found to perform better with minutiae points with large amount of translation, and the computational time was less than that of LMBA and the MPBA approaches. However, the memory usage required in DRBA and MPBA for the accumulator array is greater than memory required in LMBA.enFingerprintsFingerprint alignment algorithmsRotationArticleMlambo, C., Mathekga, M. E., & Nelwamondo, F. V. (2014). A study of Hough Transform-based fingerprint alignment algorithms. http://hdl.handle.net/10204/8052Mlambo, CS, Mmamolatelo E Mathekga, and Fulufhelo V Nelwamondo "A study of Hough Transform-based fingerprint alignment algorithms." (2014) http://hdl.handle.net/10204/8052Mlambo C, Mathekga ME, Nelwamondo FV. A study of Hough Transform-based fingerprint alignment algorithms. 2014; http://hdl.handle.net/10204/8052.TY - Article AU - Mlambo, CS AU - Mathekga, Mmamolatelo E AU - Nelwamondo, Fulufhelo V AB - This paper classifies existing Hough Transform fingerprint alignment algorithms and compares their performance to determine the one that gives optimal alignment results (translation and rotation). The classification is performed by considering the implementation of each algorithm. The comparison is performed by considering the alignment results computed using each group of algorithms when varying number of minutiae points, rotation angle, and translation. In addition, the memory usage, computing time and accuracy are taken into consideration. The experiments were performed on a small database where fingerprints were captured in different orientations and locations and on the public database FVC2004. Three classes of Hough Transform-Based approaches were classified as the Local Match Based Alignment(LMBA), Discretized Rotation Based Alignment(DRBA) and Matching Pair Based Alignment (MPBA). The results revealed good accuracy on all three approaches, however, the computing time and memory usage affected the performance of each approach. The LMBA approach perform better than the DRBA and the MPBA approaches on minutiae points set with larger rotation and small number of points. The DRBA approach was found to perform better with minutiae points with large amount of translation, and the computational time was less than that of LMBA and the MPBA approaches. However, the memory usage required in DRBA and MPBA for the accumulator array is greater than memory required in LMBA. DA - 2014-10 DB - ResearchSpace DP - CSIR KW - Fingerprints KW - Fingerprint alignment algorithms KW - Rotation LK - https://researchspace.csir.co.za PY - 2014 SM - 0975 8887 T1 - A study of Hough Transform-based fingerprint alignment algorithms TI - A study of Hough Transform-based fingerprint alignment algorithms UR - http://hdl.handle.net/10204/8052 ER -