TY - JOUR AU - Alsuhimat, Fadi Mohammad AU - Mohamad, Fatma Susilawati TI - A Hybrid Method of Feature Extraction for Signatures Verification Using CNN and HOG a Multi-Classification Approach JF - IEEE ACCESS J2 - IEEE ACCESS VL - 11 PY - 2023 SP - 21873 EP - 21882 PG - 10 SN - 2169-3536 DO - 10.1109/ACCESS.2023.3252022 UR - https://m2.mtmt.hu/api/publication/33892456 ID - 33892456 AB - The offline signature verification system's feature extraction stage is regarded as crucial and has a significant impact on how well these systems perform because the quantity and calibration of the features that are extracted determine how well these systems can distinguish between authentic and fake signatures. In this study, we introduced a hybrid method for extracting features from signature images, wherein a Convolutional Neural Network (CNN) and Histogram of Oriented Gradients (HOG) were used, followed by the feature selection algorithm (Decision Trees) to identify the key features. Finally, the CNN and HOG methods were combined. Three classifiers were employed to evaluate the efficacy of the hybrid method (long short-term memory, support vector machine, and K-nearest Neighbor). The experimental findings indicated that our suggested model executed satisfactorily in terms of efficiency and predictive ability, with accuracies of (95.4%, 95.2%, and 92.7%) the UTSig dataset, and (93.7%, 94.1%, and 91.3%, respectively) with the CEDAR dataset. This accuracy is deemed to be of high significance, particularly given that we checked skilled forged signatures that are more difficult to recognize than other forms of forged signatures like (simple or opposite). LA - English DB - MTMT ER - TY - JOUR AU - Ajij, Md AU - Pratihar, Sanjoy AU - Nayak, Soumya Ranjan AU - Hanne, Thomas AU - Roy, Diptendu Sinha TI - Off-line signature verification using elementary combinations of directional codes from boundary pixels JF - NEURAL COMPUTING & APPLICATIONS J2 - NEURAL COMPUT APPL PY - 2021 PG - 18 SN - 0941-0643 DO - 10.1007/s00521-021-05854-6 UR - https://m2.mtmt.hu/api/publication/32394123 ID - 32394123 AB - Verifying the genuineness of official documents, such as bank checks, certificates, contract forms, bonds, etc., remains a challenging task when it comes to accuracy and robustness. Here, the genuineness is related to the degree of match of the signature contained in the documents relating to the original signatures of the authorized person. Signatures of authorized persons are considered known in advance. In this paper, a novel feature set is introduced based on quasi-straightness of boundary pixel runs for signature verification. We extract the quasi-straight line segments using elementary combinations of the directional codes from the signature boundary pixels and subsequently we obtain the feature set from various quasi-straight line classes. The quasi-straight line segments provide a blending of straightness and small curvatures resulting in a robust feature set for the verification of signatures. We have used Support Vector Machine (SVM) for classification and have shown results on standard signature datasets like CEDAR (Center of Excellence for Document Analysis and Recognition) and GPDS-100 (Grupo de Procesado Digital de la Senal). The results establish how the proposed method outperforms the existing state of the art. LA - English DB - MTMT ER - TY - JOUR AU - Diaz, Moises AU - Ferrer, Miguel A. AU - Ramalingam, Soodamani AU - Guest, Richard TI - Investigating the Common Authorship of Signatures by Off-Line Automatic Signature Verification Without the Use of Reference Signatures JF - IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY J2 - IEEE T INF FOREN SEC VL - 15 PY - 2020 SP - 487 EP - 499 PG - 13 SN - 1556-6013 DO - 10.1109/TIFS.2019.2924195 UR - https://m2.mtmt.hu/api/publication/31076867 ID - 31076867 AB - In automatic signature verification, questioned specimens are usually compared with reference signatures. In writer-dependent schemes, a number of reference signatures are required to build up the individual signer model while a writer-independent system requires a set of reference signatures from several signers to develop the model of the system. This paper addresses the problem of automatic signature verification when no reference signatures are available. The scenario we explore consists of a set of signatures, which could be signed by the same author or by multiple signers. As such, we discuss three methods which estimate automatically the common authorship of a set of off-line signatures. The first method develops a score similarity matrix, worked out with the assistance of duplicated signatures; the second uses a feature-distance matrix for each pair of signatures; and the last method introduces pre-classification based on the complexity of each signature. Publicly available signatures were used in the experiments, which gave encouraging results. As a baseline for the performance obtained by our approaches, we carried out a visual Turing Test where forensic and non-forensic human volunteers, carrying out the same task, performed less well than the automatic schemes. LA - English DB - MTMT ER - TY - JOUR AU - Diaz, Moises AU - Ferrer, Miguel A. AU - Impedovo, Donato AU - Malik, Muhammad Imran AU - Pirlo, Giuseppe AU - Plamondon, Rejean TI - A Perspective Analysis of Handwritten Signature Technology JF - ACM COMPUTING SURVEYS J2 - ACM COMPUT SURV VL - 51 PY - 2019 IS - 6 PG - 39 SN - 0360-0300 DO - 10.1145/3274658 UR - https://m2.mtmt.hu/api/publication/31076868 ID - 31076868 AB - Handwritten signatures are biometric traits at the center of debate in the scientific community. Over the last 40 years, the interest in signature studies has grown steadily, having as its main reference the application of automatic signature verification, as previously published reviews in 1989, 2000, and 2008 bear witness. Ever since, and over the last 10 years, the application of handwritten signature technology has strongly evolved and much research has focused on the possibility of applying systems based on handwritten signature analysis and processing to a multitude of new fields. After several years of haphazard growth of this research area, it is time to assess its current developments for their applicability in order to draw a structured way forward. This perspective reports a systematic review of the last 10 years of the literature on handwritten signatures with respect to the new scenario, focusing on the most promising domains of research and trying to elicit possible future research directions in this subject. LA - English DB - MTMT ER - TY - JOUR AU - Wang, Mei AU - Zhai, Ke AU - Liu, Chi Harold AU - Li, Yujie TI - A Mobile Computing Method Using CNN and SR for Signature Authentication with Contour Damage and Light Distortion JF - WIRELESS COMMUNICATIONS & MOBILE COMPUTING J2 - WIREL COMMUN MOB COM PY - 2018 PG - 10 SN - 1530-8669 DO - 10.1155/2018/5412925 UR - https://m2.mtmt.hu/api/publication/27566330 ID - 27566330 LA - English DB - MTMT ER - TY - JOUR AU - Hamouchene, Izem AU - Aouat, Saliha TI - Efficient approach for iris recognition JF - SIGNAL IMAGE AND VIDEO PROCESSING J2 - SIGNAL IMAGE VIDEO PROCES VL - 10 PY - 2016 IS - 7 SP - 1361 EP - 1367 PG - 7 SN - 1863-1703 DO - 10.1007/s11760-016-0900-y UR - https://m2.mtmt.hu/api/publication/26220159 ID - 26220159 LA - English DB - MTMT ER - TY - JOUR AU - Serdouk, Yasmine AU - Nemmour, Hassiba AU - Chibani, Youcef TI - New off-line Handwritten Signature Verification method based on Artificial Immune Recognition System JF - EXPERT SYSTEMS WITH APPLICATIONS J2 - EXPERT SYST APPL VL - 51 PY - 2016 SP - 186 EP - 194 PG - 9 SN - 0957-4174 DO - 10.1016/j.eswa.2016.01.001 UR - https://m2.mtmt.hu/api/publication/26034458 ID - 26034458 LA - English DB - MTMT ER - TY - JOUR AU - Shaheen, Sara AU - Rockwood, Alyn AU - Ghanem, Bernard TI - SAR: Stroke Authorship Recognition JF - COMPUTER GRAPHICS FORUM J2 - COMPUT GRAPH FORUM VL - 35 PY - 2016 IS - 6 SP - 73 EP - 86 PG - 14 SN - 0167-7055 DO - 10.1111/cgf.12733 UR - https://m2.mtmt.hu/api/publication/26390215 ID - 26390215 LA - English DB - MTMT ER - TY - JOUR AU - Favorskaya, Margarita AU - Baranov, Roman ED - NevesSilva, R ED - Tshirintzis, GA ED - Uskov, V ED - Howlett, RJ ED - Jain, LC TI - The Off-line Signature Verification Based on Structural Similarity JF - FRONTIERS IN ARTIFICIAL INTELLIGENCE AND APPLICATIONS J2 - FRONT ARTIF INTELL APPL VL - 262 PY - 2014 SP - 421 EP - 430 PG - 10 SN - 0922-6389 DO - 10.3233/978-1-61499-405-3-421 UR - https://m2.mtmt.hu/api/publication/24902777 ID - 24902777 LA - English DB - MTMT ER - TY - CONF AU - Jarad, M AU - Al-Najdawi, N AU - Tedmori, S TI - Offline handwritten signature verification system using a supervised neural network approach T2 - 2014 6th International Conference on Computer Science and Information Technology, CSIT 2014 PB - IEEE Computer Society PB - IEEE Computer Society PY - 2014 SP - 189 EP - 195 PG - 7 DO - 10.1109/CSIT.2014.6805999 UR - https://m2.mtmt.hu/api/publication/25056249 ID - 25056249 N1 - A4 LA - English DB - MTMT ER - TY - JOUR AU - Wen, Jing MoHan Chen AU - JiaXin, Ren TI - Off-Line Signature Verification Based on Local Structural Pattern Distribution Features JF - PATTERN RECOGNITION J2 - PATTERN RECOGN VL - 484 PY - 2014 SP - 499 EP - 507 PG - 9 SN - 0031-3203 UR - https://m2.mtmt.hu/api/publication/24767048 ID - 24767048 LA - English DB - MTMT ER - TY - THES AU - Ghali, Bassma TI - Variability of Handwriting Biomechanics. A Focus on Grip Kinetics during Signature Writing TS - A Focus on Grip Kinetics during Signature Writing PY - 2013 SP - 143 UR - https://m2.mtmt.hu/api/publication/24767050 ID - 24767050 LA - English DB - MTMT ER - TY - CHAP AU - Malik, MI AU - Liwicki, M AU - Alewijnse, L AU - Ohyama, W AU - Blumenstein, M AU - Found, B TI - ICDAR2013 Competitions on Signature Verification and Writer Identification for On- and Offline Skilled Forgeries (SigWiComp2013) T2 - PROC INT CONF DOC PB - IEEE CY - Washington DC T3 - 12th International Conference on Document Analysis and Recognition(ICDAR), ISSN 1520-5363 PB - IEEE PY - 2013 SP - 1477 EP - 1483 PG - 7 DO - 10.1109/ICDAR.2013.220 UR - https://m2.mtmt.hu/api/publication/24561060 ID - 24561060 LA - English DB - MTMT ER - TY - CONF AU - Partouche, CNE Franck AU - Rosny, Sous Bois TI - Questioned Documents T2 - 17th Interpol International Forensic Science Managers Symposium PY - 2013 SP - 854 EP - 897 PG - 44 UR - https://m2.mtmt.hu/api/publication/24767047 ID - 24767047 LA - English DB - MTMT ER -