Online Signature Verification in Stationary Wavelet Transform Domain
Subject Areas : electrical and computer engineering
1 - Tarbiat Modares University
2 - Tarbiat Modares University
Abstract :
In this paper, an online signature verification method using extended regression in stationary wavelet domain is presented. To calculate the similarity between two signatures by extended regression, we should equalize the time length of the corresponding signals in two signatures. Using all points of the signals to equalize their time length will decrease the difference between a genuine signature and its forgery. Here a new approach based on the extreme points warping of the signals is presented. This approach equalizes the time length of two signals without degrading the differences between them. Also we calculated the similarity of signatures by using the details of the signals in stationary wavelet transform, SWT, domain, which showed very good results. The proposed system was tested on SVC2004 signature database. The results were compared with the results of participant teams in the first international signature verification competition. We have gained EER=6% for skilled forgery signatures. Comparing the result, it shows that we stand in the second rank between all the participants. This system has no verification error for random forgery signatures and stands in the first rank. Our experimental results show that using SWT domain instead of time domain decreases the verification error rate by 35%.
[1] G. K. Gupta, R. Joyce, "Using position extrema points to capture shape in on-line handwritten signature verification," Pattern Recognition, vol. 40, no. 10, pp. 2811-2817, Oct. 2007.
[2] A. Kholmatov and B. Yanikoglu, "Identity authentication using improved online Signature verification method," Pattern Recognition, vol. 26, no. 15, pp. 2400-2408, No. 2005.
[3] L. Nanni, "Experimental comparison of one-class classifiers for online signature verification," Neurocomputing, vol. 69, no. 7-9, pp. 869-873, Mar. 2006.
[4] L. Lee, T. Berger, and E. Aviczer, "Reliable on-line human signature verification systems," IEEE Trans. on Pattern Anal. and Mach. Intel., vol. 18, no. 6, pp. 643-647, Jun. 1996.
[5] R. Plamondon and G. Lorette, "Automatic signature verification and writer identification the state of the art," Pattern Recogntion, vol. 22, no. 2, pp. 107-131, 1989.
[6] H. Lei and V. Govindaraju, "A comparative study on the consistency of features in on-line signature verification," Pattern Recognition Letters, vol. 26, no. 15, pp. 2483-2489, Nov. 2005.
[7] J. Fierrez, J. Ortega - Garcia, D. Ramos, and J. Gonzalez, "HMM-based on-line signature verification: feature extraction and signature modeling," Pattern Recognition Letters, vol. 28, no. 16, pp. 2325-2334, 1 Dec. 2007.
[8] J. Lee, H. Yoon, J. Sob, B. Chon, and Y. K. Chong, "Using geometric extrema for segment-to-segment characteristics comparison in online signature verification," Pattern Recognition, vol. 37, no. 1, pp. 93-103, Jan. 2004.
[9] H. Feng and C. Wah, "Online signature verification using a new extreme points warping technique," Pattern Recognition, vol. 24, no. 16, pp. 2943-2951, Dec. 2003.
[10] H. Lei, S. Palla, and V. Govindaraju, "ER2: an intuitive similarity measure for on-line signature verification," in Proc. 9th Int. Workshop on Frontiers in Handwriting Recognition. IWFHR9, pp. 191-195, Tokyo, 26-29 Oct. 2004.
[11] I. Nakanishi, H. Sakamoto, Y. Itoh, and Y. Fukui, "Multi - matcher online signature verification system in DWT domain," in Proc. Int. Conf. on Acoustics, Speech, and Signal Processing, vol. 2, pp. 965-968, Mar. 2005.
[12] A. da Silva and D. S. de Freitas, "Wavelet-based compared to function - based on - line signature verification," in Proc. 15th Brazilian Symposium on Computer Diagramics and Image Processing, IBGRAPI'02), pp. 218-225, Fortaleza-CE, Brazil, 7-10 Oct. 2002.
[13] A. Jain, F. Griess, and S. Connell, "On-line signature verification," Pattern Recognition, vol. 35, no. 12, pp. 2963-2972, Dec. 2002.
[14] C. E. Keog, "Making time-series classification more accurate using learned constraints," in Proc. Intl. Conf. on Data Mining, pp. 11-22, Lake Buena Vista, Florida, US, 22-24, Aug. 2004.
[15] م. وليزاده و ا. کبير، "تطابق فرينههاي سيگنالهاي امضاهاي برخط به روش DTW براي حفظ تمايز بين امضاهاي اصلي و جعلي،" اولين کنگره مشترک سيستمهاي فازي و سيستمهاي هوشمند، جلد 1، صص. 712-707، مشهد، 9-7 شهريور 1386.
[16] م. ولي زاده، استفاده از رگرسيون توسعهيافته در حوزه تبديل موجک براي تأييد امضاي برخط، پاياننامه کارشناسي ارشد، دانشگاه تربيت مدرس تهران، صص. 63-55، 1386.
[17] م. وليزاده و ا. کبير، "استفاده از تبديل موجک براي بهبود سيستم تأييد امضاي برخط،" سيزدهمين کنفرانس سالانه کامپيوتر ايران، کيش، 21-19 اسفند 1386.
[18] The First International Signature Verification Competition, 2004, (SVC2004), available in http://www.cse.ust.hk/svc2004/