Approaches and Issues in Offline Signature Verification System

Saikia, Hemanta; Sarma, Kamal

doi:10.5120/5780-8035

Cited by 13 publications

(8 citation statements)

References 31 publications

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“…TanH method gives the optimum result as it includes a numerous parameters. Z-score & Min-Max are easy and simple to implement but they are more prone to presence of outliers [17]. The result obtained for each modality is then fused using weighted sum-rule and on account of outcome after fusion, the decisionis taken comparing to the ser threshold value.…”

Section: Fusion Methodologymentioning

confidence: 99%

An Improved Multi Biometric System for Authentication

Sharma¹,

Sivaramkumar²

2019

IJEAT

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Biometrics is the new technology for calculating and measuring the body parts of a person. It is playing an important role in identifying an individual. It signifies a metrics related to person characteristics (physiological or behavioral). Biometric system may be based on single modal or multiple modals. Multimodal system also termed as multi-biometric system (hybrids two or more modals) are becoming popular. The idea behind the paper is to implement and improve the authentication processusing multiple trait for identifying a person. Here, the combination of Iris & Fingerprint based biometric model is presented. The relevant features (key-points) are extracted from these two traits in parallel and then they are passed through matching module. The key-points are extracted using Discrete Wavelet Transform (DWT) and Speeded-Up Robust Feature (SURF) descriptor and then passed to the matching (mapping) module where mapping is done using the Normalized Weighted Sum-Rule. The experimental result showed that the proposed multi-biometric model performs well showing clear variation in FAR and FRR against the existing models.

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Section: Fusion Methodologymentioning

confidence: 99%

An Improved Multi Biometric System for Authentication

Sharma¹,

Sivaramkumar²

2019

IJEAT

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“…Signature is human identifier biometrics that is well known and recognized as a tool for identifying a person [1]. A signature is a handwriting or hand stroke with a unique writing style, such as a line of stroke that resembles the name of the signature owner or symbol used as proof of an individual's identity.…”

Section: Introductionmentioning

confidence: 99%

“…Offline Signature identification is considered more difficult than online signature since offline signature does not have a dynamic feature that is present on online signature [1]. Offline signatures depend only on the capture signature shape available from the signature image, while online signatures can use various features such as pressure points and velocity of the drawn signature [3].…”

Section: Introductionmentioning

confidence: 99%

Offline Signature Identification Using Deep Learning and Euclidean Distance

Nugraha

Nurhadiyatna²,

Arsa

2021

LKJITI

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Hand signature is one of human characteristic that human have since birth, which can be used as identity recognition. A high accuracy signature recognition is needed to identify the right owner of signature. This study present signature identification using a combination method between Deep Learning and Euclidean Distance. 3 different signature datasets are used in this study which consist of SigComp2009, SigComp2011, and private dataset. Signature images preprocessed using binary image conversion, Region of Interest, and thinning. Several testing scenarios is applied to measure proposed method robustness, such as usage of various Pretrained Deep Learning, dataset augmentation, and dataset split ratio modifier. The best accuracy achieved is 99.44% with high precision rate.

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“…Biometric system attributes help gauge their effectiveness. Most biometric systems may not cater to the basic necessary attributes, making Fingerprint verification a challenging area in pattern recognition of biometric systems [1]. This technology is the base for numerous new inventions.…”

Section: Introductionmentioning

confidence: 99%

An analysis of issues in biometric finger identification

Veerasamy

2014

IJET

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A Person's identity is an essential factor in this vastly connected society. Biometric Finger has wide acceptance as a genuine method for determining an individual's identity. Biometric Finger authentication is reliable, since physical characteristics in humans are difficult to forge, harder to change or make copies. Biometric fingerprinting is one of the most popular and legally accepted biometrics used in person identification. Finger print authentication applications include Computer Applications, Network Access, Data Protection, Transaction Security, and Web Security. Ecommerce and E-governments can carry out strong authentication rules. This paper analyzes issues related to Fingerprint identification to suggest viable alternatives.

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Approaches and Issues in Offline Signature Verification System

Cited by 13 publications

References 31 publications

An Improved Multi Biometric System for Authentication

An Improved Multi Biometric System for Authentication

Offline Signature Identification Using Deep Learning and Euclidean Distance

An analysis of issues in biometric finger identification

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