Chernyshova et al., 2019 - Google Patents
Optical font recognition in smartphone-captured images and its applicability for ID forgery detectionChernyshova et al., 2019
View PDF- Document ID
- 5241218998430331477
- Author
- Chernyshova Y
- Aliev M
- Gushchanskaia E
- Sheshkus A
- Publication year
- Publication venue
- Eleventh International Conference on Machine Vision (ICMV 2018)
External Links
Snippet
In this paper, we consider the problem of detecting counterfeit identity documents in images captured with smartphones. As the number of documents contain special fonts, we study the applicability of convolutional neural networks (CNNs) for detection of the conformance of the …
- 238000001514 detection method 0 title abstract description 14
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Singh et al. | A survey of OCR applications | |
| Lee et al. | A survey on banknote recognition methods by various sensors | |
| Chernyshova et al. | Optical font recognition in smartphone-captured images and its applicability for ID forgery detection | |
| Roy et al. | Machine-assisted authentication of paper currency: an experiment on Indian banknotes | |
| Akbari et al. | A novel database for automatic processing of Persian handwritten bank checks | |
| Das et al. | Multi‐script versus single‐script scenarios in automatic off‐line signature verification | |
| Cruz et al. | Categorization of document image tampering techniques and how to identify them | |
| Liu et al. | MRZ code extraction from visa and passport documents using convolutional neural networks | |
| Ghanmi et al. | CheckSim: A reference-based identity document verification by image similarity measure | |
| Eskenazi et al. | When document security brings new challenges to document analysis | |
| Medvedev et al. | Towards facial biometrics for id document validation in mobile devices | |
| Tornés et al. | Detecting forged receipts with domain-specific ontology-based entities & relations | |
| Hassan et al. | A survey on techniques of detecting identity documents forgery | |
| Bouma et al. | Authentication of travel and breeder documents | |
| Shabaninia et al. | SUT: a new multi-purpose synthetic dataset for Farsi document image analysis | |
| Sundravadivelu et al. | Extensive Analysis of IoT Assisted Fake Currency Detection using Novel Learning Scheme | |
| Banerjee et al. | Quote examiner: verifying quoted images using web-based text similarity | |
| Rajalingam | Text Segmentation and Recognition for Enhanced Image Spam Detection: An Integrated Approach | |
| Xu et al. | PSFNet: A Deep Learning Network for Fake Passport Detection | |
| Costa et al. | Cork as a unique object: Device, method, and evaluation | |
| Longjam et al. | Improving reliability of manipuri offline signature verification using writer independent paradigms | |
| Kodirov et al. | Music with harmony: chord separation and recognition in printed music score images | |
| Rahmat et al. | Braille letter recognition in deep convolutional neural network with horizontal and vertical projection | |
| Khandan | An intelligent hybrid model for identity document classification | |
| Bouma et al. | Combatting fraud on travel, identity, and breeder documents |