Abstract
The analysis of dynamic laser speckle is widely known as an effective non-contact technique for detecting micro-activity on a sample surface. However, the analysis obtained using conventional statistical methods is heavily influenced by the properties of the sample, laser beam and ambient lighting. Recently, we proposed a new normal vector based dynamic speckle analysis method and demonstrated its ability to remove interference due to non-uniform reflectivity, illumination, and time-varying ambient lighting. In this paper, the normal vector based statistical technique for dynamic speckle analysis is further justified by the application to leaf surface micro-motion detection for monitoring plant water status. We carried out experiments for surface activity detection of attached leaves to monitor variation of leaf water status. The presented results highlight the advantage of the normal vector based analysis over image intensity based methods and demonstrate the potential of measuring plant water status via dynamic laser speckle analysis.
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