Writer's identification by using word reason feature transform

Patil, Prashant Madhukar; Wagh, R. B.

doi:10.1109/icetets.2016.7602992

Cited by 1 publication

(1 citation statement)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Here, as suggested by Easwaramoorthy et al (2016), and Eliabeth et al (2015), the value of the person's feature or the intra-class, should be lower than that of different persons or the inter-class. Additionally, features with the least similarity error for one person in a pair of twins (intra-class) and the most similarity error for both individuals in a pair of twins (inter-class) demonstrate the soundness as well as acceptableness of individual features (Patil and Wagh, 2016). This shows the need to obtain the individual features from the samples of handwritten-fingerprint to allow the identification of the individual in a pair of twins.…”

Section: Individuality Of Twins Multi-biometricmentioning

confidence: 99%

A Multimodal Biometric System using Global Features for Identical Twins Identification

Mohammed

Shamsuddin

2018

Journal of Computer Science

View full text Add to dashboard Cite

Pattern recognition studies are currently focusing on twin's biometric identification. The system of twins' biometric Identification can potentially differentiate the individual's biometric pattern. With the new Unimodal biometric identification, identical twins are precisely and reliably identified, with well exposure of certain traits. However, it is much more challenging to identify identical twins as they share so many similarities between them, as opposed to identifying the non-twins. Therefore, this study proposes the use of more than one biometric trait with global features. Pattern recognition application includes extracting and selecting meaningful features and this has brought to the key question in twin handwriting-fingerprint identification: How to obtain features from many writing styles and shapes of twin handwritingfingerprint in order that the reflection of the right person between twins can be obtained. Global with Aspect United Moment Invariant for the extractions of global feature using the identical twin multi-biometric identification is thus proposed by this study.

show abstract

Section: Individuality Of Twins Multi-biometricmentioning

confidence: 99%