Signature Recognition Based on Discrete Wavelet Transform
DOI:
https://doi.org/10.21928/uhdjst.v3n1y2019.pp19-29Keywords:
Biometrics System, Off-line Signature Recognition, Feature Extraction, Discrete Wavelet TransformAbstract
Personal identification is an actively developing area of research. Human signature is a vital biometric attribute which can be used to authenticate human identity. There are many approaches to recognize signature with a lot of researches. The aim of this research is to introduce an efficient approach for signature recognition. This approach starts with the process the acquired signatures and stores these signatures in the database to be ready for verification. The collection of signature data based on collecting samples of 10 people and 10 signatures for each person through traditional ink stamp method. These signatures are digitized to be ready for processing. Many steps are applied to the acquired images to perform the pre-processing stage. The proposed approach based on discrete wavelet transforms to extract significant features from each signature image. Pre-processing is applied at the beginning of this approach to avoid any unwanted noise. This approach consists of many steps: Data acquisition, pre-processing, signature registration, and feature extraction. High recognition rate results (100%) are obtained through applying this approach.
References
[1]. Biometrics: Identification and Security, Source title: Multidisciplinary Perspectives in Cryptology and Information Security, 2014, DOI: 10.4018/978-1-4666-5808-0.ch014. IGI Global, Pennsylvania (USA).
[2]. Muzhir Shaban Al-Ani, Zana Azeez Kakarash, Future Aspects of Intelligent Car Parking Based on Internet of Things, UHD JOURNAL OF SCIENCE AND TECHNOLOGY, May 2018 | Vol 2 | Issue 1.
[3]. Muzhir Shaban Al-Ani, “Electrocardiogram Waveform Classification Based on P-QRS-T Wave Recognition”, UHD Journal of Science and Technology | May 2018 | Vol 2 | Issue 2.
[4]. S. Impedovo and G. Pirlo, “Verification of Handwritten Signatures : an Overview”, 14th International Conference on Image Analysis and Processing (ICIAP 2007).
[5]. A. Karouni, B. Daya, S. Bahlak, “Offline signature recognition using neural networks approach”, Procedia Computer Science 3:155-161, 2010.
[6]. M. Arathi and A. Govardhan, “An Efficient Offline Signature Verification System”, vol. 4, no. 6, 2014.
[7]. Muzhir Shaban Al-Ani, “Study the Characteristics of Finite Impulse Response Filter Based on Modified Kaiser Window”, UHD Journal of Science and Technology, August 2017. Vol 1, Issue 2. PP. 1-6.
[8]. V. Malik and A. Arora, “Signature Recognition Using Matlab 1”, vol. 3, no. Vi, pp. 682–687, 2015.
[9]. Bhavani M. ThuraisinghamLatifur KhanMehedy MasudKevin W. Hamlen, “Data Mining for Security Applications”, Conference: 2008 IEEE/IPIP International Conference on Embedded and Ubiquitous Computing (EUC 2008), Shanghai, China, December 17-20, 2008.
[10]. Sorin Soviany, Sorin Puscoci, Virginia Sandulescu, Cristina Soviany. (2018) A Biometric Security Model for Mobile Applications. International Journal of Communications, 3, 85-92.
[11]. Muzhir Al-Ani, Biometric Security, Source title: Handbook of Research on Threat Detection and Countermeasures in Network Security, 2015, DOI: 10.4018/978-1-4666-6583-5.ch011, IGI Global, Pennsylvania (USA).
[12]. Ahmed M. OmarNagia M. GhanemMohamed A. IsmailSahar M. Ghanem (2015), “Arabic-Latin Offline Signature Recognition Based on Shape Context Descriptor”, International Conference on Computer Vision Systems, ICVS 2015: Computer Vision Systems pp 24-33
[13]. R. Jana, R. Saha, D. Datta, “Offline Signature Verification using Euclidian Distance”, International Journal of Computer Science and Information Technologies, Vol. 5 (1) , 2014, 707-710.
[14]. H. M. El-bakry and N. Mastorakis, “Personal Identification Through Biometric Technology, AIC'09 Proceedings of the 9th WSEAS international conference on Applied informatics and communications Pages 325-340.
[15]. Srikanta Pal, Michael Blumenstein and Umapada Pal. Automatic off-Line Signature Verification Systems: A Review. IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET) (14):20-27, 2011.
[16]. Saba Mushtaq, Ajaz H Mir, “N Signature verification: A study”, Conference: 2013 4th International Conference on Computer and Communication Technology (ICCCT).
[17]. S. Bhatia, P. Bhatia, D. Nagpal, S. Nayak (2013), “Online Signature Forgery Prevention”, International Journal of Computer Applications 75(13):21-29.
[18]. M A Maurello, Jennifer A. Clarke, R. S. Ackley (2008), Signature Characteristics in Contact Calls of the White-Nosed Coati”, Journal of Mammalogy 81(2):415-421.
[19]. V. A. Bharadi, H. B Kekre (2010) “Off-Line Signature Recognition Systems”, International Journal of Computer Applications 1(27).
[20]. M. Tomar P. Singh, “An Intelligent Network for Offline Signature Verification Using Chain Code", International Conference on Computer Science and Information Technology CCSIT 2011: Advanced Computing pp 10-22.
[21]. Mehdi Radmehr, Seyed Mahmoud Anisheh, Mohsen Nikpour and Abbas Yaseri (2011) Designing an Offline Method for Signature Recognition”, World Applied Sciences Journal 13 (3): 438-443, 2011.
[22]. M. V. Kanawade and S. S. Katariya, “Signature Verification & Recognition – Case Study”, International Journal of Electronics, Communication & Instrumentation Engineering Research and Development (IJECIERD) ISSN 2249-684X, Vol. 3, Issue 1, Mar 2013, 77-86.
[23]. H. Hiary, R. Alomari, T. Kobbaey, R. Z. Al-Khatib, Al-Zu’Bi, and H. Hasan, “Off-line signature verification system based on DWT and common features extraction”, J. Theor. Appl. Inf. Technol., vol. 51, no. 2, pp. 165–174, 2013.
[24]. M. V Kanawade, S. S. Katariya, “Review of Offline Signature Verification and Recognition System”, Int. J. Emerg. Technol. Adv. Eng., vol. 3, no. 7, pp. 659–662, 2013.
[25]. I. Bhattacharya, P. Ghosh, and S. Biswas, “Offline Signature Verification Using Pixel Matching Technique”, Procedia Technol., vol. 10, pp. 970–977, 2013.
[26]. R. Doroz, M. Palys, T. Orczyk, H. Safaverdi, “Method of Signature Recognition With the Use of the Complex Features”, vol. 23, pp. 1–8, 2014.
[27]. M. S. Shekhawat, “A review paper on Glass-Ceramics”, Int. J. Mater. Phys., vol. 6, no. 1, pp. 1–6, 2015.
[28]. Muzhir Shaban Al-Ani and Maha Mahmoud Al-Saidi, “An Improved Proposed Approach for handwritten Arabic Signature Recognition”, Advances in Computer Science and Engineering, India, Volume 7, Issue 1, pp. 25-35 (August 2011).
[29]. L. G. Hafemann, R. Sabourin, and L. S. Oliveira, “Offline Handwritten Signature Verification - Literature Review”, Computer Vision and Pattern Recognition, 978-1-5386-1842-4/17/$31.00 c 2017 IEEE.
[30]. H. Hedjaz, R. Djemili, B. Hocine “Signature recognition using binary features and KNN”, International Journal of Biometrics 10(1):1, January 2018.
[2]. Muzhir Shaban Al-Ani, Zana Azeez Kakarash, Future Aspects of Intelligent Car Parking Based on Internet of Things, UHD JOURNAL OF SCIENCE AND TECHNOLOGY, May 2018 | Vol 2 | Issue 1.
[3]. Muzhir Shaban Al-Ani, “Electrocardiogram Waveform Classification Based on P-QRS-T Wave Recognition”, UHD Journal of Science and Technology | May 2018 | Vol 2 | Issue 2.
[4]. S. Impedovo and G. Pirlo, “Verification of Handwritten Signatures : an Overview”, 14th International Conference on Image Analysis and Processing (ICIAP 2007).
[5]. A. Karouni, B. Daya, S. Bahlak, “Offline signature recognition using neural networks approach”, Procedia Computer Science 3:155-161, 2010.
[6]. M. Arathi and A. Govardhan, “An Efficient Offline Signature Verification System”, vol. 4, no. 6, 2014.
[7]. Muzhir Shaban Al-Ani, “Study the Characteristics of Finite Impulse Response Filter Based on Modified Kaiser Window”, UHD Journal of Science and Technology, August 2017. Vol 1, Issue 2. PP. 1-6.
[8]. V. Malik and A. Arora, “Signature Recognition Using Matlab 1”, vol. 3, no. Vi, pp. 682–687, 2015.
[9]. Bhavani M. ThuraisinghamLatifur KhanMehedy MasudKevin W. Hamlen, “Data Mining for Security Applications”, Conference: 2008 IEEE/IPIP International Conference on Embedded and Ubiquitous Computing (EUC 2008), Shanghai, China, December 17-20, 2008.
[10]. Sorin Soviany, Sorin Puscoci, Virginia Sandulescu, Cristina Soviany. (2018) A Biometric Security Model for Mobile Applications. International Journal of Communications, 3, 85-92.
[11]. Muzhir Al-Ani, Biometric Security, Source title: Handbook of Research on Threat Detection and Countermeasures in Network Security, 2015, DOI: 10.4018/978-1-4666-6583-5.ch011, IGI Global, Pennsylvania (USA).
[12]. Ahmed M. OmarNagia M. GhanemMohamed A. IsmailSahar M. Ghanem (2015), “Arabic-Latin Offline Signature Recognition Based on Shape Context Descriptor”, International Conference on Computer Vision Systems, ICVS 2015: Computer Vision Systems pp 24-33
[13]. R. Jana, R. Saha, D. Datta, “Offline Signature Verification using Euclidian Distance”, International Journal of Computer Science and Information Technologies, Vol. 5 (1) , 2014, 707-710.
[14]. H. M. El-bakry and N. Mastorakis, “Personal Identification Through Biometric Technology, AIC'09 Proceedings of the 9th WSEAS international conference on Applied informatics and communications Pages 325-340.
[15]. Srikanta Pal, Michael Blumenstein and Umapada Pal. Automatic off-Line Signature Verification Systems: A Review. IJCA Proceedings on International Conference and workshop on Emerging Trends in Technology (ICWET) (14):20-27, 2011.
[16]. Saba Mushtaq, Ajaz H Mir, “N Signature verification: A study”, Conference: 2013 4th International Conference on Computer and Communication Technology (ICCCT).
[17]. S. Bhatia, P. Bhatia, D. Nagpal, S. Nayak (2013), “Online Signature Forgery Prevention”, International Journal of Computer Applications 75(13):21-29.
[18]. M A Maurello, Jennifer A. Clarke, R. S. Ackley (2008), Signature Characteristics in Contact Calls of the White-Nosed Coati”, Journal of Mammalogy 81(2):415-421.
[19]. V. A. Bharadi, H. B Kekre (2010) “Off-Line Signature Recognition Systems”, International Journal of Computer Applications 1(27).
[20]. M. Tomar P. Singh, “An Intelligent Network for Offline Signature Verification Using Chain Code", International Conference on Computer Science and Information Technology CCSIT 2011: Advanced Computing pp 10-22.
[21]. Mehdi Radmehr, Seyed Mahmoud Anisheh, Mohsen Nikpour and Abbas Yaseri (2011) Designing an Offline Method for Signature Recognition”, World Applied Sciences Journal 13 (3): 438-443, 2011.
[22]. M. V. Kanawade and S. S. Katariya, “Signature Verification & Recognition – Case Study”, International Journal of Electronics, Communication & Instrumentation Engineering Research and Development (IJECIERD) ISSN 2249-684X, Vol. 3, Issue 1, Mar 2013, 77-86.
[23]. H. Hiary, R. Alomari, T. Kobbaey, R. Z. Al-Khatib, Al-Zu’Bi, and H. Hasan, “Off-line signature verification system based on DWT and common features extraction”, J. Theor. Appl. Inf. Technol., vol. 51, no. 2, pp. 165–174, 2013.
[24]. M. V Kanawade, S. S. Katariya, “Review of Offline Signature Verification and Recognition System”, Int. J. Emerg. Technol. Adv. Eng., vol. 3, no. 7, pp. 659–662, 2013.
[25]. I. Bhattacharya, P. Ghosh, and S. Biswas, “Offline Signature Verification Using Pixel Matching Technique”, Procedia Technol., vol. 10, pp. 970–977, 2013.
[26]. R. Doroz, M. Palys, T. Orczyk, H. Safaverdi, “Method of Signature Recognition With the Use of the Complex Features”, vol. 23, pp. 1–8, 2014.
[27]. M. S. Shekhawat, “A review paper on Glass-Ceramics”, Int. J. Mater. Phys., vol. 6, no. 1, pp. 1–6, 2015.
[28]. Muzhir Shaban Al-Ani and Maha Mahmoud Al-Saidi, “An Improved Proposed Approach for handwritten Arabic Signature Recognition”, Advances in Computer Science and Engineering, India, Volume 7, Issue 1, pp. 25-35 (August 2011).
[29]. L. G. Hafemann, R. Sabourin, and L. S. Oliveira, “Offline Handwritten Signature Verification - Literature Review”, Computer Vision and Pattern Recognition, 978-1-5386-1842-4/17/$31.00 c 2017 IEEE.
[30]. H. Hedjaz, R. Djemili, B. Hocine “Signature recognition using binary features and KNN”, International Journal of Biometrics 10(1):1, January 2018.
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Published
2019-05-16
How to Cite
Muhamad, S. S., & Al-Ani, M. S. (2019). Signature Recognition Based on Discrete Wavelet Transform. UHD Journal of Science and Technology, 3(1), 19–29. https://doi.org/10.21928/uhdjst.v3n1y2019.pp19-29
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