Classification of Images Background Subtraction in Image Segmentation

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10331401" target="_blank" >RIV/00216208:11320/16:10331401 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Classification of Images Background Subtraction in Image Segmentation

Original language description

Many image segmentation algorithms have been proposed to partition an image into foreground regions of interest and background regions to be ignored. These algorithms use pixel intensities to partition the image, so it should be good practice to choose an appropriate background color as different as possible from the foreground one. In the case of a unique digitizing operation the user can make the choice of background color by himself in order to obtain a good result in the segmentation process, but in the case of several digitizing operations it would be useful to automate the whole process by removing any decision of the user about the choice of background color. Furthermore modern instruments allow capturing images with a high resolution characterized by a huge number of pixels, and pose speed problems to the image segmentation algorithms based on an idea of local thresholding. In this work an approach that adapts a widely used method for detecting moving objects from a video, called background subtraction (foreground detection), to the image segmentation framework is introduced. This approach combines local and global thresholding techniques to take advantage of the computational efficiency of the former and the accuracy of the latter. It provides good results in segmentation, and allows automating the process when foreground color of images is not constant, as well as speeding it up significantly. An application to the real data concerning botanical seeds is presented in order to compare, from a statistical perspective, the results derived from the proposed approach with those provided by standard image segmentation methods.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BB - Applied statistics, operational research

OECD FORD branch

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Project

<a href="/en/project/GA15-09663S" target="_blank" >GA15-09663S: Modeling dynamic financial processes with structural breaks</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2016

Confidentiality

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

Name of the periodical

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

ISSN

0231-9721

e-ISSN

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Volume of the periodical

55

Issue of the periodical within the volume

1

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

14

Pages from-to

73-86

UT code for WoS article

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EID of the result in the Scopus database

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