Dual Palm Print-Based Human Recognition Using Fusion

2021 ◽  
pp. 101-109
Author(s):  
Milind Rane ◽  
Umesh Bhadade
Keyword(s):  
Human Recognition ◽  
Palm Print

A Review on Palm Print Recognition Techniques

2017 ◽  
Vol 7 (3) ◽  
pp. 196-201 ◽  
Author(s):  
Vivek kr. Sharma ◽  
◽  
Nisha Vasudeva ◽  
Keyword(s):  
Palm Print

Human Double Embeddedness

2018 ◽  
Author(s):  
Natalia Marandiuc
Keyword(s):  
Charles Taylor ◽  
Human Beings ◽  
Human Recognition ◽  
Authentic Self ◽  
Human Subjectivity

The chapter proposes that human beings are conditioned by a double embeddedness: humans are immersed in inescapable frameworks of meaning and shaped by relationships of significance. In dialogue with Charles Taylor, the chapter discusses how these two elements are constitutive features of human subjectivity and how they relate to each other. In order to operate, subjectivity needs a horizon of meaning, which accrues in relationships of attachment that, in turn, thrive under the canopy of common meaning. After discussing the specificity of one such framework, the culture of authenticity, the chapter delves more deeply into one of its paradoxical dimensions: recognition. It is shown how human recognition from loving others is an ineliminable trait for an authentic self, the implication of which is that relationships of significance constitute relational homes that “house” the human self as it grows and flourishes and as it heals when broken.

scholarly journals Optimized Periocular Template Selection for Human Recognition

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Sambit Bakshi ◽  
Pankaj K. Sa ◽  
Banshidhar Majhi
Keyword(s):  
Feature Extraction ◽  
Biometric System ◽  
Human Recognition ◽  
Novel Approach ◽  
Database Size ◽  
Periocular Region ◽  
Template Selection ◽  
Selection For ◽  
Computationally Intensive

A novel approach for selecting a rectangular template around periocular region optimally potential for human recognition is proposed. A comparatively larger template of periocular image than the optimal one can be slightly more potent for recognition, but the larger template heavily slows down the biometric system by making feature extraction computationally intensive and increasing the database size. A smaller template, on the contrary, cannot yield desirable recognition though the smaller template performs faster due to low computation for feature extraction. These two contradictory objectives (namely, (a) to minimize the size of periocular template and (b) to maximize the recognition through the template) are aimed to be optimized through the proposed research. This paper proposes four different approaches for dynamic optimal template selection from periocular region. The proposed methods are tested on publicly available unconstrained UBIRISv2 and FERET databases and satisfactory results have been achieved. Thus obtained template can be used for recognition of individuals in an organization and can be generalized to recognize every citizen of a nation.

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