Field temperature measurement technique using the flow visualization with the liquid crystal has been investigated and is applied to the three-dimensional temperature measurement by scanning the thermometry. The color to temperature calibration of the liquid crystal is carried out using the neural networks, where the effect of view angle relative to the light sheet is considered by distributing the networks over the image plane and with an optimum smoothing technique. The calibration error of temperature due to the view angle is much reduced by the present technique and is proved to be useful by application to the temperature measurement of the thermal convection over a heated surface. The three-dimensional temperature distributions of the thermal convection is reconstructed from the measured temperature field and the structure of thermal plumes is examined.

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