Evaluation of laser dynamic speckle signals applying granular computing

The laser dynamic speckle phenomenon is a grained and fluctuant interference produced when a laser light is reflected from an illuminated surface undergoing some kind of activity. This phenomenon allows developing practical applications of unlimited use in biology and technology for being a non-destructive process, enabling the detection of not easily observable activities, such as seeds viability, paints drying, bacteria activities, corrosion processes, food decomposition, fruits bruising, etc.Sequences of intensity images are obtained in order to evaluate the phenomena dynamics, and the signals generated by the intensity changes in each pixel through the sequence are processed with the finality of identifying underlying activity in each point.This paper offers a new methodology based on granular computing to characterize the signals dynamics within the time domain, reducing the time processing and proposing news evaluation parameters to characterize speckle patterns.The methodology is applicable to stationary and non-stationary cases, enabling to monitor the phenomenon in almost real time. Two dynamic processes are analyzed to assess the goodness of the proposed methodology: fast paint drying (non-stationary) and corn seed viability (stationary), being obtained results in agreement with the physical behaviour of the observed processes.