Publication detail

Comparison of methods for flow border detection in images of smoke visualization

CALETKA, P. PECH, O. JEDELSKÝ, J. LÍZAL, F. JÍCHA, M.

Original Title

Comparison of methods for flow border detection in images of smoke visualization

English Title

Comparison of methods for flow border detection in images of smoke visualization

Type

conference paper

Language

en

Original Abstract

A separation of the flow region from the surroundings is an essential step in the analysis of smoke visualization images. The separation can be performed using several detection methods from the image segmentation group. This paper deals with the border detection of the air flow downstream of a benchmark automotive vent using different threshold-based detection methods. An assessment of the methods on the basis of the resulting image quality is also addressed. The quality level depends on the quantity and brightness of disturbances in the background area. The disturbance is usually an isolated region of smoke, which naturally cannot be a part of the flow. Three representative images of different quality levels were selected for the detection, and three methods were used for the evaluation. Each of the methods was used to determine the threshold differently (by the level, by the ratio, and by the change of brightness). It is demonstrated that the change-based method with an appropriately selected parameter is the most convenient for images with the worst quality level while level- and ratio-based methods are only applicable for images of good quality.

English abstract

A separation of the flow region from the surroundings is an essential step in the analysis of smoke visualization images. The separation can be performed using several detection methods from the image segmentation group. This paper deals with the border detection of the air flow downstream of a benchmark automotive vent using different threshold-based detection methods. An assessment of the methods on the basis of the resulting image quality is also addressed. The quality level depends on the quantity and brightness of disturbances in the background area. The disturbance is usually an isolated region of smoke, which naturally cannot be a part of the flow. Three representative images of different quality levels were selected for the detection, and three methods were used for the evaluation. Each of the methods was used to determine the threshold differently (by the level, by the ratio, and by the change of brightness). It is demonstrated that the change-based method with an appropriately selected parameter is the most convenient for images with the worst quality level while level- and ratio-based methods are only applicable for images of good quality.

Keywords

Car vent, smoke visualization, border detection

Released

28.03.2016

Publisher

EDP Sciences

Location

Francie

Pages from

1

Pages to

4

Pages count

4

URL

Full text in the Digital Library

BibTex


@inproceedings{BUT119741,
  author="Petr {Caletka} and Ondřej {Pech} and Jan {Jedelský} and František {Lízal} and Miroslav {Jícha}",
  title="Comparison of methods for flow border detection in images of smoke visualization",
  annote="A separation of the flow region from the surroundings is an essential step in the analysis of smoke visualization images. The separation can be performed using several detection methods from the image segmentation group. This paper deals with the border detection of the air flow downstream of a benchmark automotive vent using different threshold-based detection methods. An assessment of the methods on the basis of the resulting image quality is also addressed. The quality level depends on the quantity and brightness of disturbances in the background area. The disturbance is usually an isolated region of smoke, which naturally cannot be a part of the flow. Three representative images of different quality levels were selected for the detection, and three methods were used for the evaluation. Each of the methods was used to determine the threshold differently (by the level, by the ratio, and by the change of brightness). It is demonstrated that the change-based method with an appropriately selected parameter is the most convenient for images with the worst quality level while level- and ratio-based methods are only applicable for images of good quality.",
  address="EDP Sciences",
  booktitle="EPJ Web of Conferences",
  chapter="119741",
  doi="10.1051/epjconf/201611402009",
  howpublished="online",
  institution="EDP Sciences",
  year="2016",
  month="march",
  pages="1--4",
  publisher="EDP Sciences",
  type="conference paper"
}