An Autoadaptive Edge-Detection Algorithm for Flame and Fire Image Processing

Qiu, Tian and Yan, Yong and Lu, Gang (2012) An Autoadaptive Edge-Detection Algorithm for Flame and Fire Image Processing. IEEE Transactions on Instrumentation and Measurement, 61 (5). pp. 1486-1493. ISSN 0018-9456. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1109/TIM.2011.2175833

Abstract

The determination of flame or fire edges is the process of identifying a boundary between the area where there is thermochemical reaction and those without. It is a precursor to image-based flame monitoring, early fire detection, fire evaluation, and the determination of flame and fire parameters. Several traditional edge-detection methods have been tested to identify flame edges, but the results achieved have been disappointing. Some research works related to flame and fire edge detection were reported for different applications; however, the methods do not emphasize the continuity and clarity of the flame and fire edges. A computing algorithm is thus proposed to define flame and fire edges clearly and continuously. The algorithm detects the coarse and superfluous edges in a flame/fire image first and then identifies the edges of the flame/fire and removes the irrelevant artifacts. The autoadaptive feature of the algorithm ensures that the primary symbolic flame/fire edges are identified for different scenarios. Experimental results for different flame images and video frames proved the effectiveness and robustness of the algorithm.

Item Type: Article
Uncontrolled keywords: Edge detection, feature extraction, fire, flame, image edge analysis, image processing, monitoring, shape measurement.
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image Analysis, Image Processing
Divisions: Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: J. Harries
Date Deposited: 25 Apr 2012 14:31
Last Modified: 07 Apr 2014 11:29
Resource URI: http://kar.kent.ac.uk/id/eprint/29339 (The current URI for this page, for reference purposes)
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