Polarization-sensitive digital holography for quality control of textile fibers

Proving the authenticity and quality of garments is not a trivial task. The risk of clothes counterfeiting depends on the difficulty in distinguishing precious textile fibers. One of the most precious and luxurious textile fibers is cashmere, which can be morphologically similar to standard sheep wool fibers. This simplifies adulteration in the textile market. To counteract fraudulent practices and to guarantee product integrity, a reliable discrimination pipeline should be adopted in the textile industries as fiber pureness control before clothes production. However, traditional methods for fiber analysis rely on naked-eye observation under light microscopes, which is a time-consuming process, prone to errors and heavily dependent on expert operators. These techniques often fail to provide consistent and trustworthy results due to significant overlaps in morphological characteristics of different fibers, such as fiber diameter and surface roughness. Addressing these limitations requires innovative approaches capable of improving both accuracy and efficiency. Polarization-sensitive digital holography (PS-DH) offers a novel microscopy solution in this field. This technology demonstrated its effectiveness in distinguishing synthetic fibers from natural ones, such as cotton and wool, further highlighting its potential in diverse textile applications. By combining polarization-based optical measurements with advanced machine learning algorithms, we can discriminate between similar textile fibers. Polarization-sensitive analysis introduces unique information channels, like birefringence, which complement morphological features, allowing the identification of subtle interclass differences that are otherwise difficult to detect. This study demonstrates the potential of a PS-DH system to revolutionize textile fiber analysis by automatizing the classification process and reducing manual inspection.