Using Composite Sinusoidal Patterns in Structured-Illumination Reflectance Imaging (SIRI) for Enhanced Detection of Defects in Food

Abstract

Abstract. This study presented a first exploration of using composite sinusoidal patterns that integrated two and three spatial frequencies of interest, in structured-illumination reflectance imaging (SIRI) for enhanced detection of defects in food (e.g., bruises in apples). Three methods based on Fourier transform were proposed to retrieve amplitude images at different frequencies by using either phase shifting with or without spiral phase transform (SPT) or frequency-domain filtering. The phase-shifting method involves solving a linear system that is composed of multiple phase-shifted pattern images in the Fourier space, and SPT that acts as a two-dimensional quadrature transform operator is used to reduce the images needed for amplitude retrieval; while the filtering-based method directly extracts different frequency components from only one pattern image that are then subjected to SPT processing. The three methods were tested for dual-frequency and triple-frequency composite sinusoidal patterns through numerical simulations and experiments on the detection of fresh bruises in apples by. The phase-shifting methods showed good performance in terms of small demodulation errors and strong image contrast for bruise detection; the filtering-based method, although viable in numerical simulation, needed improvement due to the worst practical performance. In addition, more frequency components involved would deteriorate the performance of these methods, and grid composite patterns were superior over the fringe ones due to reduced interactions between different frequency components.