Levenberg-Marquardt Variants in Chrominance-Based Skin Tissue Detection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F19%3A50015941" target="_blank" >RIV/62690094:18450/19:50015941 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-030-17935-9_9" target="_blank" >http://dx.doi.org/10.1007/978-3-030-17935-9_9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-17935-9_9" target="_blank" >10.1007/978-3-030-17935-9_9</a>

Result language

angličtina

Original language name

Levenberg-Marquardt Variants in Chrominance-Based Skin Tissue Detection

Original language description

Levenberg-Marquardt method is a very useful tool for solving nonlinear curve fitting problems; while it is also a very promising alternative of weight adjustment in feed forward neural networks. Forcing the Hessian matrix to stay positive definite, the parameter λ also turns the algorithm into the well-known variations: steepest-descent and Gauss-Newton. Given the computation time, the results achieved by these methods surely differ while minimizing the sum of squares of errors and with an acceptable accuracy rate in skin tissue recognition. Therefore in this paper, we propose the implementation of these variations in network training by a set of tissue samples borrowed from SFA human skin database. The RGB images taken from the set are converted into YCbCr color space and the networks are individually trained by these methods to create weight arrays minimizing the error squares between the pixel values and the function output. Consisting of hands on computer keyboards, the images are analyzed to find skin tissues for achieving high accuracy with low computation time and for comparison of the methods.

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

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2019

Confidentiality

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

Article name in the collection

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ISBN

978-3-030-17934-2

ISSN

0302-9743

e-ISSN

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Number of pages

12

Pages from-to

87-98

Publisher name

Springer Verlag

Place of publication

Berlin

Event location

Granada

Event date

Oct 8, 2019

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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