The quantified fuel mass distribution of a spray was obtained from laser induced fluorescence images with optical patternation. In the dense spray region, however, the emitted fluorescence signal is significantly attenuated in the path of the detector because of particle scattering. Thus, the fluorescence image obtained with a camera may be different from the true fluorescence image pattern. Therefore, we propose a method of finding the geometric mean of the intensities obtained with two cameras and apply it to a solid-cone spray. We also compared this optical patternation technique with other spray measurement techniques, such as, PDPA (Phase Doppler Particle Analyzer) and the mechanical patternator, to validate the accuracy of the proposed method. Results show that the quantified mass distribution of the optical patternator agrees well with those of the PDPA and the mechanical patternator. Hence, we can estimate the local mass distribution rapidly without determining the entire structure of the spray by using the geometric mean of the signals obtained from two cameras.
A 3D reconstruction technique from stereo images that requires minimal intervention from the user has been developed. The reconstruction problem consists of three steps of estimating specific geometry groups. The first step is estimating the epipolar geometry that exists between the stereo image pairs which includes feature matching in both images. The second is estimating the affine geometry, a process to find a special plane in the projective space by means of vanishing points. The third step, which includes camera self-calibration, is obtaining a metric geometry from which a 3D model of the scene could be obtained. The major advantage of this method is that the stereo images do not need to be calibrated for reconstruction. The results of camera calibration and reconstruction have shown the possibility of obtaining a 3D model directly from features in the images.
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