Tuneable algorithms for tracking activity images in dynamic speckle applications

•Several algorithms have been proposed to show the dynamic speckle activity. However, there is no single algorithm that is useful for all applications, and several must usually be tested for a certain measurement.•Now, we present a generalized algorithm for processing activity speckle images. We propose a new algorithm that offers an improvement on current algorithms, and a new approach based on a generalization of the addition and subtraction complex operations. These operations allow selective control of contrast and smoothing of image results. This approach can also be applied to other existing algorithms, thereby increasing their flexibility. We described and demonstrated the new proposed algorithm, and the way in which tuning can be introduced and used in other descriptors. We show qualitative segmentation in speckle images and calculate quantitative measurements of the results for different angles of the proposed algorithm to show the improvements on an objective basis. Examples are given of typical test cases such as reading under an obstructing media such as paper or papyrus, and activity in corn seeds and ultrasound images. We mentioned potential applications in other branches of industry and engineering. Herein we present a generalized algorithm for processing activity images. Existing algorithms are applicable only to particular cases, and a new, broader approach is therefore proposed here that is based on a set of tuneable filters for images, using an extension of the addition and subtraction operations. The choice of tuning parameter is determined based on the desired result in each experimental case. We include several objective criteria to guide the choice of the most suitable value for the parameter. The use of our approach is exemplified with typical images with dynamic speckle, such as reading under paper, corn seeds and ultrasound images. These examples are also potentials applications in engineering environments.