Using composite sinusoidal patterns in structured-illumination reflectance imaging (SIRI) for enhanced detection of apple bruise

摘要

Structured-illumination reflectance imaging (SIRI) provides a new means for enhanced detection of defects in horticultural products. Implementing the technique relies on retrieving amplitude images by illuminating the object with sinusoidal patterns of single spatial frequencies, which, however, are limited in interrogating the tissues at different depths. This study presented a first exploration of using composite sinusoidal patterns that integrated two and three spatial frequencies of interest, in 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 patterns through numerical simulations and experiments on the detection of fresh bruises in apples by SIRI. 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 introduced in the pattern 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. (C) 2016 Elsevier Ltd. All rights reserved.