The data reduction for different Speckle images using MATLAB and IMAGE pro-plus

When coherent light rays can be incident on an optically rough object it will scatter randomly through all directions. Interference of these scattered rays leads to the formation of a bright spots (constructive interference), and dark spots (destructive interference), these are called Laser Speckles.

THE DATA REDUCTION USING MATLAB FOR DIFFERENT SPECKLE IMAGES FORM SMALL SURFACES ROUGHNESS

The so-called laser speckles are bright spots and dark spots formed when a coherent ray is incident on a rough surface which scattered randomly in all directions, the interference of these scattered rays form these bright and dark spots (Laser Speckles).In this paper we are concerned with the formation of Objective speckles calculations. Using MATLAB the image can be converted into binary object (0 and 1) as the speckle spots intensities are dark and bright, respectively.To simplify the calculations, two processes (transform and predictive) may be used, and according to the loss of many data for the using of predictive process, the transform process is considered.The calculations are based on the evaluation on small roughness of surfaces in range 0.1 – 1 μm, on the same footing the contrast was considered in the range from zero to one.Fraunhofer diffraction Unfortunately, no calculations in this field had been done from other researchers.

Robustness of Laser Speckles as Unique Traceable Markers of Metal Components

The traceability of manufactured components is growing in importance with the greater use of digital service solutions offered and with an increased digitalization of manufacturing logistics. In this paper, we investigate the use of image-plane laser speckles as a tool to acquire a unique code from the surface of the component and the ability to use this pattern as a secure component-specific digital fingerprint. Intensity correlation is used as a numerical identifier. Metal sheets of different materials and steel pipes are considered. It is found that laser speckles are robust against surface alterations caused by surface compression and scratching and that the correct pattern reappears from a surface contaminated by oil after cleaning. In this investigation, the detectability is close to 100% for all surfaces considered, with zero false positives. The exception is a heavily oxidized surface wiped by a cotton cloth between recordings. It is further found that the main source for lost detectability is caused by misalignment between the registration and detection geometries where a positive match is lost by a change in angle in the order of 60 mrad. Therefore, as long as the registration and detection systems, respectively, use the same optical arrangement, laser speckles have the ability to serve as unique component identifiers without having to add extra markings or a dedicated sensor to the component.