عنوان المقالة:تحديد التوقيع المكتوب بخط اليد استنادًا إلى نموذج MobileNets ومصنف آلة المتجهات الداعمة Handwritten signature identification based on MobileNets model and support vector machine classifier
Israa Bashir Mohammed, Bashar Saadoon Mahdi, Mustafa Salam Kadhm
الملخص الانجليزي
Biometrics is a field that uses behavioral and biological traits to identify/verify a person. Characteristics include handwrittien signature, iris, gait, and fingerprint. Signature-based biometric systems are common due to their simple collection and non-intrusive. Identify the humans using their handwritten signatures has received an important attention in several modern crucial applications such as in automatic bank check, law-enforcements, and historical documents processing. Therefore, in this paper an accurate handwritten signatures system is proposed. The system uses a proposed preprocessing stage for the input handwritten signatures images. Besides, a new deep learning model called MobileNets, which used for classification process. Support vector machine (SVM) used as a classifier with the MobileNets inorder to get a better identifaction results. Experimental results conducted on standard CEDAR, ICDER, sigcomp handwritten signature datasets report 99.8%, 98.2%, 99.5%, identification accuracy, respectively.
تاريخ النشر
01/08/2023
الناشر
Bulletin of Electrical Engineering and Informatics
أ.م.د مصطفى سلام كاظم | Mustafa Salam Kadhm | 16206