Imaging‐Based Metrics Drawn from Visual Perception of Haze and Clarity of Materials. I. Method, Analysis, and Distance‐Dependent Transparency. Issue 5 (24th March 2021)

• Record Type: Journal Article
• Authors: Busato, Stephan; Kremer, Daniel; Perevedentsev, Aleksandr
• Is Part Of: Macromolecular materials and engineering. Volume 306:Issue 5(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-03-24
• Subjects: clarifying agents -- clarity -- haze -- light scattering -- optical properties -- roughness -- transparency; Plastics -- Periodicals; Polymers -- Periodicals; Polymerization -- Periodicals; 547.705
• DOI: 10.1002/mame.202100045
• Languages: English
• ISSNs: 1438-7492

Abstract

Abstract: A versatile imaging‐based method is presented for quantifying the transparency of materials based on "illumination diffusion" (ID), representing scattering‐ and refraction‐induced change in the spatial distribution of transmitted light intensity. Samples are backlit through a graticule mask, with analysis performed by comparative evaluation of graticule images recorded as‐is and viewed through a sample, mimicking visual perception. ID‐haze is quantified as the reduction of contrast, while ID‐sharpness is derived from imaged knife‐edge acuity. Measurements are performed for diverse materials, including clarified polyolefins, silica‐filled amorphous polymers, semicrystalline films, and etched polymer sheets. Comparisons with the respective haze and clarity values obtained using a common ASTM D1003 haze‐meter are made in terms of their quantitative correlation and suitability for applications. In particular, unlike conventional instruments, ID‐based analysis captures the variation of transparency with sample‐to‐object "airgap" distance. Gratifyingly, ID‐haze generally features a one‐to‐one correlation with standard ASTM haze, when determined at a specific distance. The presented method also enables sensitive detection of local defects—differentiating them from large‐area characteristics—and accurately extracts the contribution of luminescence to loss of transparency. ID‐based method therewith offers unique opportunities for application‐ and airgap‐specific transparency analysis, and advanced options for optical process‐ and quality control. Abstract : A versatile imaging‐based method is presented for quantifying transparency of materials. 'Haze' and 'sharpness' metrics are explicitly derived from visual perception attributes, namely contrast and resolution of fine detail. Unlike conventional analysis based on ASTM D1003, the method quantifies the variation of transparency with sample‐to‐object 'airgap' distance and enables spatially‐resolved measurements. The method is therefore optimally suited for sensitive optical quality‐ and process control.