A comparative study on chrominance based methods in dorsal hand recognition: Single image case

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F18%3A50014705" target="_blank" >RIV/62690094:18450/18:50014705 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/chapter/10.1007/978-3-319-92058-0_68" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-92058-0_68</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-92058-0_68" target="_blank" >10.1007/978-3-319-92058-0_68</a>

Result language

angličtina

Original language name

A comparative study on chrominance based methods in dorsal hand recognition: Single image case

Original language description

Dorsal hand recognition is a crucial topic in biometrics and human-machine interaction; however most of the identification systems identify and segment the hands from the images consisting of high contrast backgrounds. In other words, capturing and analyzing images of hands on a white or black or any colored background is way too easy to achieve high accuracy. On the contrary, in continuous authentication or in interactive human-machine systems, it can be not possible nor feasible to process high contrast images, like hands on computer keyboards which is not as simple as single color backgrounds even the feature to be extracted is solely the hand color. Therefore we deal with processing of the images consisting of hands on computer keyboards to compare various luminance and chrominance methods by YCbCr color space extraction and to find ways to achieve higher accuracy without any succeeding erosion, dilation or filtering. The methods focused on chromatic intervals could be summarized as: fixed intervals, covariance intervals and fuzzy 2-means. Our main contribution briefly is a necessary accuracy comparison and validation of the common methods on the single images. The highest accuracy is found as 96% by fuzzy 2-means applied to chrominance layers of the image.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2018

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Lecture notes in computer science

ISBN

978-3-319-92057-3

ISSN

0302-9743

e-ISSN

neuvedeno

Number of pages

11

Pages from-to

711-721

Publisher name

Springer

Place of publication

Cham

Event location

Montreal

Event date

Jun 25, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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