Detecting Fraudulent Bank Checks

Chhabra, Saheb; Gupta, Garima; Gupta, Manju Lata; Gupta, Gaurav

doi:10.1007/978-3-319-67208-3_14

Cited by 9 publications

(4 citation statements)

References 12 publications

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“…They have also analyzed printed security features on currency notes. Chhabra et al [2] have developed a method for detecting fraudulent bank checks, including checks whose text has been altered using invisible ink. However, this method for alteration detection does not work well for printed documents.…”

Section: Related Workmentioning

confidence: 99%

Quick Response Encoding of Human Facial Images for Identity Fraud Detection

Singh¹,

Chhabra

Gupta

et al. 2019

Advances in Digital Forensics XV

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Advancements in printing and scanning technology enable fraudsters to tamper with identity documents such as identity cards, drivers' licenses, admit cards, examination hall tickets and academic transcripts. Several security features are incorporated in important identity documents to counter forgeries and verify genuineness, but these features are often lost in printed versions of the documents. At this time, a satisfactory method is not available for authenticating a person's facial image (photograph) in a printed version of a document. Typically, an official is required to check the person's image against an image stored in an online verification database, which renders the problem even more challenging.This chapter presents an automated, low-cost and efficient method for addressing the problem. The method employs printed quick response codes corresponding to low-resolution facial images to authenticate the original and printed versions of identity documents.

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Section: Related Workmentioning

confidence: 99%

Quick Response Encoding of Human Facial Images for Identity Fraud Detection

Singh¹,

Chhabra

Gupta

et al. 2019

Advances in Digital Forensics XV

Self Cite

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“…The Cristo Salvador corpus is a 19th century Spanish manuscript provided by Biblioteca Valenciana Digital (Bi-ValDi), and it is publicly available for research purposes on the website of the Pattern Recognition and Human Language Technology (PRHLT) research center 1 . It is a single writer book composed of 53 pages (the page 41 is presented in Figure 3)…”

Section: Historical Manuscript: the Cristo Salvador Corpusmentioning

confidence: 99%

“…Many documents used every day include handwritten text and, in many cases, such as for detecting fraudulent bank checks [1], it would be interesting to recognise these text images automatically. However, state-of-the-art handwritten text recognition (HTR) systems can not suppress the need of human supervision when high quality transcriptions are needed [2,3,4,5].…”

Section: Introductionmentioning

confidence: 99%

Improving Transcription of Manuscripts with Multimodality and Interaction

Granell¹,

Martínez-Hinarejos²,

Romero³

2018

IberSPEECH 2018

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State-of-the-art Natural Language Recognition systems allow transcribers to speed-up the transcription of audio, video or image documents. These systems provide transcribers an initial draft transcription that can be corrected with less effort than transcribing the documents from scratch. However, even the drafts offered by the most advanced systems based on Deep Learning contain errors. Therefore, the supervision of those drafts by a human transcriber is still necessary to obtain the correct transcription. This supervision can be eased by using interactive and assistive transcription systems, where the transcriber and the automatic system cooperate in the amending process. Moreover, the interactive system can combine different sources of information in order to improve their performance, such as text line images and the dictation of their textual contents. In this paper, the performance of a multimodal interactive and assistive transcription system is evaluated on one Spanish historical manuscript. Although the quality of the draft transcriptions provided by a Handwriting Text Recognition system based on Deep Learning is pretty good, the proposed interactive and assistive approach reveals an additional reduction of transcription effort. Besides, this effort reduction is increased when using speech dictations over an Automatic Speech Recognition system, allowing for a faster transcription process.

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“…Pradheepan Raghavan and Neamat El Gayar, 2019 reported a general way to perform the fraud detection using machine learning and deep learning. Saheb Chhabra et al, 2017 reported a method used to detect fraudulent bank checks. Abd-ElZaher, 2014 discussed certain inks' affection to physically erased handwriting in fraud checks.…”

Section: Introductionmentioning

confidence: 99%

Using Multi Adaptive Neuro Fuzzy Inference Systems to Identify Fraud Bank Checks

2023

Proceedings of the 16 Th International Conference on ICT, Society and Human Beings (ICT 2023), the 15 Th International Conferen

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This research is to use multiple Adaptive Neuro Fuzzy Inference Systems (ANFIS) to design and build an image processing algorithm to quickly and easily detect a fraud or altered bank check in real time. With the help of MATLAB Fuzzy Logic and Image Processing Toolboxes, this algorithm can be used to quickly detect most fraud or altered bank checks via an ATM scanner when a fraud or altered check is deposited to an ATM. The testing and validation processes have been performed to confirm the effectiveness and correctness of this detecting algorithm. The current correct detecting rate is about 80% for checks deposited via ATMs.

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Detecting Fraudulent Bank Checks

Cited by 9 publications

References 12 publications

Quick Response Encoding of Human Facial Images for Identity Fraud Detection

Quick Response Encoding of Human Facial Images for Identity Fraud Detection

Improving Transcription of Manuscripts with Multimodality and Interaction

Using Multi Adaptive Neuro Fuzzy Inference Systems to Identify Fraud Bank Checks

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