We present a dynamic laser speckle method to easily discriminate filamentous fungi from motile bacteria in soft surfaces, such as agar plate. The method allows the detection and discrimination between fungi and bacteria faster than with conventional techniques. The new procedure could be straightforwardly extended to different micro-organisms, as well as applied to biological and biomedical research, infected tissues analysis, and hospital water and wastewaters studies.
Biospeckle patterns are named also "boiling" speckles due to its dynamic appearance. This activity takes place when the
sample changes its properties due to diverse causes. This phenomenon is characteristic of biological samples and of the
some industrial process. There are many descriptors that have been developed to characterize biospeckle patterns. This
paper presents some approaches to compare and evaluate a set of time domain descriptors using a controlled experiment.
Chemotaxis has a meaningful role in several fields, such as microbial physiology, medicine and biotechnology. We present a new application of dynamic laser speckle (or biospeckle) to detect different degrees of bacterial motility during chemotactic response experiments. Encouraging results showed different bacterial dynamic responses due to differences in the hardness of the support in the swarming plates. We compare this method to a conventional technique that uses white light. Both methods showed to be analogous and, in some cases, complementary. The results suggest that biospeckle processed images can be used as an alternative method to evaluate bacterial chemotactic response and can supply additional information about the bacterial motility in different areas of the swarm plate assay that might be useful for biological analysis.
In this work we present to methods to evaluate activity in low dynamic speckle patterns. The first one is based on the
behavior analysis of the vortices associated to the pattern. The other one consists in binarizing the speckle image. The
speckle grain areas, also called islands, experiment displacements and deformations. The variations of the island features
were analyzed with the aim of finding a correlation with the activity of the speckle pattern. Both methods were evaluated
in numerical simulations and controlled experiments. From the obtained results, it was possible to conclude that the
developed methods can be very useful for the analysis of low activity speckle patterns with some advantages with other
Dynamic speckle is a useful technique to show biological tissue activity and evolving processes in industry. There are several algorithms for quantitative and qualitative characterization of dynamic speckle. We use the statistical method receiver operating characteristic (ROC) to compare some speckle algorithms. We estimate the capacity of these descriptors to discriminate different activities and the smallest number of images necessary for a correct description of the phenomena. We also use the ROC curves to estimate the best conditions required by some activities. The results are verified using an activity image.
Dynamic speckle images are useful tools to characterize the activity of biological tissues. In this paper, this technique was applied to determine chemotaxis responses of Pseudomonas aeruginosa towards attractants. Generalized weighted differences, wavelet entropy and spectral bands decomposition algorithms were used to characterize the speckle activity. Experimental results show regions with different bacterial activity. Dynamic speckle method exhibits a good performance for this application.
Dynamic speckle or biospeckle is observed in biological samples illuminated by laser light. The properties and applications of this phenomenon have been treated in the literature. In this paper, we present a method of dynamic speckle analysis based on the filtering in frequency bands of the temporary history of each pixel. Butterworth filters are applied to the temporary evolution and different images are constructed showing the energy in each frequency band. Applications on vegetable specimens examples are shown.
Algorithms used to process a speckle image are limited by the resolution of the CCD camera and the employed digitalization system. We propose the use of dithering procedures to increase the intensity discrimination and improve the contrast resolution. This technique consists in decreasing the quantification error by performing several measurements to which a random value is added in each measurement before detection. Hence, it is possible to find a more approximated value to the real one. The precision increase results from the use of multiple images to which a determined white-light intensity has been added. This work shows the results of applying dithering to improve the precision of methods that use speckle contrast. It is a frequently used quantity in the implementation of activity images and in the determination of surface roughness. Numerically simulated images were used to verify the reliability of the technique whose intensities were later quantified for processing. The observed mean squared error is lower when this technique is employed, and the level of improvement depends on the size of the used windows. A device for the experimental verification of the results is in the design stage.