Optical Fiber Imaging Based Tomographic Reconstruction of Burner Flames

Hossain, Md. Moinul and Lu, Gang and Yan, Yong (2012) Optical Fiber Imaging Based Tomographic Reconstruction of Burner Flames. IEEE Transactions on Instrumentation and Measurement, 61 (5). pp. 1417-1425. ISSN 0018-9456. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

The full text of this publication is not available from this repository. (Contact us about this Publication)
Official URL


This paper presents the design, implementation, and evaluation of an optical fiber imaging based tomographic system for the 3-D visualization and characterization of a burner flame. Eight imaging fiber bundles coupled with two RGB charge-coupled device cameras are used to acquire flame images simultaneously from eight different directions around the burner. The fiber bundle has 30k picture elements and an objective lens with a 92° angle of view. The characteristic evaluation of the imaging fiber bundles and the calibration of the system were conducted to ensure the accuracy of the system. A new tomographic algorithm that combines the logical filtered back-projection and the simultaneous algebraic reconstruction technique is proposed to reconstruct the flame sections from the images. A direct comparison between the proposed algorithm and other tomographic approaches is conducted through computer simulation for different test templates and numbers of projections. The 3-D reconstruction of the cross- and longitudinal-sections of a burner flame from image projections obtained from the imaging system was also performed. The effectiveness of the imaging system and computer algorithm is assessed through experimental tests.

Item Type: Article
Uncontrolled keywords: Charge-couple device (CCD) camera, flame, imaging filter, luminosity distribution, three-dimensional reconstruction, tomography
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 13:34
Last Modified: 29 May 2014 13:23
Resource URI: https://kar.kent.ac.uk/id/eprint/29336 (The current URI for this page, for reference purposes)
  • Depositors only (login required):


Downloads per month over past year