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Proceedings Paper

Neural classification of the selected family of butterflies
Author(s): M. Zaborowicz; P. Boniecki; H. Piekarska-Boniecka; K. Koszela; W. Mueller; K. Górna; P. Okoń
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Paper Abstract

There have been noticed growing explorers' interest in drawing conclusions based on information of data coded in a graphic form. The neuronal identification of pictorial data, with special emphasis on both quantitative and qualitative analysis, is more frequently utilized to gain and deepen the empirical data knowledge. Extraction and then classification of selected picture features, such as color or surface structure, enables one to create computer tools in order to identify these objects presented as, for example, digital pictures. The work presents original computer system “Processing the image v.1.0” designed to digitalize pictures on the basis of color criterion. The system has been applied to generate a reference learning file for generating the Artificial Neural Network (ANN) to identify selected kinds of butterflies from the Papilionidae family.

Paper Details

Date Published: 21 July 2017
PDF: 7 pages
Proc. SPIE 10420, Ninth International Conference on Digital Image Processing (ICDIP 2017), 104202S (21 July 2017); doi: 10.1117/12.2281705
Show Author Affiliations
M. Zaborowicz, Poznan Univ. of Life Sciences (Poland)
P. Boniecki, Poznan Univ. of Life Sciences (Poland)
H. Piekarska-Boniecka, Poznan Univ. of Life Sciences (Poland)
K. Koszela, Poznan Univ. of Life Sciences (Poland)
W. Mueller, Poznan Univ. of Life Sciences (Poland)
K. Górna, Poznan Univ. of Life Sciences (Poland)
P. Okoń, Poznan Univ. of Life Sciences (Poland)


Published in SPIE Proceedings Vol. 10420:
Ninth International Conference on Digital Image Processing (ICDIP 2017)
Charles M. Falco; Xudong Jiang, Editor(s)

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