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A computationally-supported experimental procedure to estimate the primary dimensions of diffusion flames, using volume reconstruction from thermal imagery, is presented. The experimental setup uses a 4 × 16.94 mm radial distribution gas-burner, with a 0.8 mm nozzle diameter, a thermal imaging camera and a proprietary image processing algorithm. Flame thermal imagery was captured, using four different fuel loads, 350, 650, 950 and 1200 cc/min, from two different visualisation planes, 0° and 90°. The images were visually and qualitatively processed leaving aside the temperature measurement and favouring instead a non-dimensional temperature gradient,. Corresponding flame front structures were estimated and reconstructed employing computational geometry. The height and diameter magnitudes were measured indirectly through a reference length. The results show that atthe flame front structure separates itself from the background noise. Furthermore, when compared against available benchmarks, atand, the resulting flame coincides with the luminous and continuous flame heights, respectively. This approach yields maximum relative error of 36.54% and 18.91% for both compared geometries. When compared to image convolution and spatial density clustering procedures, this approach reduces the maximum error obtained by 47%. Based on this information, the methodology presented is considered suitable for dimensioning diffusion flames, thus, proposed as an estimation tool for the design and manufacturing of gas-fuelled appliances/devices.

Flame front reconstruction and volume estimation through computational geometry: a case study on machine vision applied to combustion systems