Finding defects in the wood by image segmentation

Authors

  • A.V. Kozhemyako Vinnytsia National Technical University
  • G.S. Kolesnik Vinnytsia National Technical University

DOI:

https://doi.org/10.31649/1681-7893-2018-36-2-20-27

Keywords:

image processing, image segmantation, binarization, thresholding

Abstract

This paper investigates one of fundamental problem in computer vision: object detection. The developed algorithm addresses important topics: image segmantation and contour analysis. The results showed good detection quality and processing speed. Also analyzed different algorithm of auto thresholding.

Author Biographies

A.V. Kozhemyako, Vinnytsia National Technical University

к.т.н., доцент кафедри Лазерної та оптикоелектронної техніки

G.S. Kolesnik, Vinnytsia National Technical University

аспірант кафедри Лазерної та оптикоелектронної техніки

References

Szeliski R. (2010). Computer Vision: Algorithms and Applications.

R. Gonzalez, R. Woods, (2012). Digital Image Processing. Technosphere

Mehmet Sezgin and Bulent Sankur, (2004). Survey over image thresholding techniques and quantitative performance evaluation, Journal of Electronic Imaging, 13, 1, 146-165. doi: 10.1117/1.1631315.

Nobuyuki Otsu, (1979). A threshold selection method from gray-level histograms, IEEE Trans. Sys., Man., Cyber., 9, 62-66. doi 10.1109/TSMC.1979.4310076.

Segmentation of images [Electronic resource] - Access to resource: https://habrahabr.ru/post/128768/.

Counting objects in a binary image. Part 1 [Electronic resource] - Access to the resource: https://habrahabr.ru/post/199244/.

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Abstract views: 239

Published

2019-07-08

How to Cite

[1]
A. Kozhemyako and G. Kolesnik, “Finding defects in the wood by image segmentation”, Опт-ел. інф-енерг. техн., vol. 36, no. 2, pp. 20–27, Jul. 2019.

Issue

Section

Systems Of Technical Vision And Artificial Intelligence, Image Processing And Pattern Recognition

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