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<p>Laser speckle imaging (LSI) is an optical tool used for non-destructive analysis, where the interference of coherent light scattered from an optically rough medium produces specklegrams. Analysing the time evolution of pixels within these specklegrams can provide qualitative and quantitative insights into spatial dynamic activity. Traditional methods for quantifying dynamic activity, such as the Time History of Speckle Pattern (THSP), often suffer from limitations in pixel selection criteria, particularly in the presence of specular reflections and spatially inhomogeneous activity. This paper presents an automated algorithm that removes specular artifacts and selects highly active diffuse pixels to generate a modified THSP matrix. The algorithm is experimentally validated through the study of non-uniform adhesive curing dynamics. Here, we show that the proposed method, without the need for cross polarizers or changes in sensor alignment, effectively quantifies dynamic activity, as evidenced by Inertia Moment values calculated from the modified THSP matrix. This work contributes to advancing LSI techniques for applications requiring precise and automated activity quantification.</p>

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Automated identification and quantification of inhomogeneous spatial dynamics in laser speckle imaging via specular artifact removal and active pixel selection

  • 期刊论文

  • 发表日期：

    2025年9月5日

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  • A. K. Sooraj Viswam,
  • A. Mujeeb

摘要

Laser speckle imaging (LSI) is an optical tool used for non-destructive analysis, where the interference of coherent light scattered from an optically rough medium produces specklegrams. Analysing the time evolution of pixels within these specklegrams can provide qualitative and quantitative insights into spatial dynamic activity. Traditional methods for quantifying dynamic activity, such as the Time History of Speckle Pattern (THSP), often suffer from limitations in pixel selection criteria, particularly in the presence of specular reflections and spatially inhomogeneous activity. This paper presents an automated algorithm that removes specular artifacts and selects highly active diffuse pixels to generate a modified THSP matrix. The algorithm is experimentally validated through the study of non-uniform adhesive curing dynamics. Here, we show that the proposed method, without the need for cross polarizers or changes in sensor alignment, effectively quantifies dynamic activity, as evidenced by Inertia Moment values calculated from the modified THSP matrix. This work contributes to advancing LSI techniques for applications requiring precise and automated activity quantification.