Page 87 - 2024-Vol20-Issue2
P. 87
83 | AlKarem, Khalid, & Ali
[4] P. Kiran, B. Parameshachari, J. Yashwanth, and [15] J. Poddar, V. Parikh, and S. K. Bharti, “Offline signa-
K. Bharath, “Offline signature recognition using im- ture recognition and forgery detection using deep learn-
age processing techniques and back propagation neuron ing,” Procedia Computer Science, vol. 170, pp. 610–617,
network system,” SN Computer Science, vol. 2, no. 3, 2020.
p. 196, 2021.
[16] V. Iranmanesh, S. M. S. Ahmad, W. A. W. Adnan, S. Yus-
[5] S. Ghandali and M. E. Moghaddam, “Off-line persian sof, O. A. Arigbabu, F. L. Malallah, et al., “Online
signature identification and verification based on image handwritten signature verification using neural network
registration and fusion.,” Journal of Multimedia, vol. 4, classifier based on principal component analysis,” The
no. 3, 2009. Scientific World Journal, vol. 2014, 2014.
[6] M. M. Yapici, A. Tekerek, and N. Topalog?lu, “Deep [17] T. M. Ghanim, M. I. Khalil, and H. M. Abbas, “Compar-
learning-based data augmentation method and signature ative study on deep convolution neural networks dcnn-
verification system for offline handwritten signature,” based offline arabic handwriting recognition,” IEEE Ac-
Pattern Analysis and Applications, vol. 24, pp. 165–179, cess, vol. 8, pp. 95465–95482, 2020.
2021.
[18] L. G. Hafemann, R. Sabourin, and L. S. Oliveira, “Learn-
[7] D. Banerjee, B. Chatterjee, P. Bhowal, T. Bhattacharyya, ing features for offline handwritten signature verifica-
S. Malakar, and R. Sarkar, “A new wrapper feature se- tion using deep convolutional neural networks,” Pattern
lection method for language-invariant offline signature Recognition, vol. 70, pp. 163–176, 2017.
verification,” Expert Systems with Applications, vol. 186,
p. 115756, 2021. [19] S. J. Gideon, A. Kandulna, A. A. Kujur, A. Diana, and
K. Raimond, “Handwritten signature forgery detection
[8] A. Y. Ebrahim, H. Kolivand, A. Rehman, M. S. M. using convolutional neural networks,” Procedia com-
Rahim, and T. Saba, “Features selection for offline hand- puter science, vol. 143, pp. 978–987, 2018.
written signature verification: state of the art,” Interna-
tional Journal of Computational Vision and Robotics, [20] R. R. Upadhyay, R. Mehta, and K. K. Singh, “Multi-
vol. 8, no. 6, pp. 606–622, 2018. dilation convolutional neural network for automatic
handwritten signature verification,” SN Computer Sci-
[9] H. Kaur and M. Kumar, “Signature identification and ence, vol. 4, no. 5, p. 476, 2023.
verification techniques: state-of-the-art work,” Jour-
nal of Ambient Intelligence and Humanized Computing, [21] T. Longjam, D. R. Kisku, and P. Gupta, “Writer indepen-
vol. 14, no. 2, pp. 1027–1045, 2023. dent handwritten signature verification on multi-scripted
signatures using hybrid cnn-bilstm: A novel approach,”
[10] K. Manjunatha, S. Manjunath, D. S. Guru, and M. So- Expert Systems with Applications, vol. 214, p. 119111,
mashekara, “Online signature verification based on 2023.
writer dependent features and classifiers,” Pattern Recog-
nition Letters, vol. 80, pp. 129–136, 2016. [22] P. Wei, H. Li, and P. Hu, “Inverse discriminative net-
works for handwritten signature verification,” in Pro-
[11] Y. H. Liu, “Feature extraction and image recognition ceedings of the IEEE/CVF Conference on Computer
with convolutional neural networks,” in Journal of Vision and Pattern Recognition, pp. 5764–5772, 2019.
Physics: Conference Series, vol. 1087, p. 062032, IOP
Publishing, 2018. [23] W. Xiao and Y. Ding, “A two-stage siamese network
model for offline handwritten signature verification,”
[12] R. Ghosh, “A recurrent neural network based deep learn- Symmetry, vol. 14, no. 6, p. 1216, 2022.
ing model for offline signature verification and recogni-
tion system,” Expert Systems with Applications, vol. 168, [24] J.-X. Ren, Y.-J. Xiong, H. Zhan, and B. Huang, “2c2s:
p. 114249, 2021. A two-channel and two-stream transformer based frame-
work for offline signature verification,” Engineering Ap-
[13] A. K. Jain, F. D. Griess, and S. D. Connell, “On-line sig- plications of Artificial Intelligence, vol. 118, p. 105639,
nature verification,” Pattern recognition, vol. 35, no. 12, 2023.
pp. 2963–2972, 2002.
[25] J. A. Lopes, B. Baptista, N. Lavado, and M. Mendes,
[14] M. Ismail and S. Gad, “Off-line arabic signature recog- “Offline handwritten signature verification using deep
nition and verification,” Pattern Recognition, vol. 33, neural networks,” Energies, vol. 15, no. 20, p. 7611,
no. 10, pp. 1727–1740, 2000. 2022.
