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Proceedings Paper

Phase analysis for three-dimensional surface reconstruction of apples using structured-illumination reflectance imaging
Author(s): Yuzhen Lu; Renfu Lu
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Paper Abstract

Three-dimensional (3-D) shape information is valuable for fruit quality evaluation. This study was aimed at developing phase analysis techniques for reconstruction of the 3-D surface of fruit from the pattern images acquired by a structuredillumination reflectance imaging (SIRI) system. Phase-shifted sinusoidal patterns, distorted by the fruit geometry, were acquired and processed through phase demodulation, phase unwrapping and other post-processing procedures to obtain phase difference maps relative to the phase of a reference plane. The phase maps were then transformed into height profiles and 3-D shapes in a world coordinate system based on phase-to-height and in-plane calibrations. A reference plane-based approach, coupled with the curve fitting technique using polynomials of order 3 or higher, was utilized for phase-to-height calibrations, which achieved superior accuracies with the root-mean-squared errors (RMSEs) of 0.027- 0.033 mm for a height measurement range of 0-91 mm. The 3rd-order polynomial curve fitting technique was further tested on two reference blocks with known heights, resulting in relative errors of 3.75% and 4.16%. In-plane calibrations were performed by solving a linear system formed by a number of control points in a calibration object, which yielded a RMSE of 0.311 mm. Tests of the calibrated system for reconstructing the surface of apple samples showed that surface concavities (i.e., stem/calyx regions) could be easily discriminated from bruises from the phase difference maps, reconstructed height profiles and the 3-D shape of apples. This study has laid a foundation for using SIRI for 3-D shape measurement, and thus expanded the capability of the technique for quality evaluation of horticultural products. Further research is needed to utilize the phase analysis techniques for stem/calyx detection of apples, and optimize the phase demodulation and unwrapping algorithms for faster and more reliable detection.

Paper Details

Date Published: 1 May 2017
PDF: 18 pages
Proc. SPIE 10217, Sensing for Agriculture and Food Quality and Safety IX, 102170G (1 May 2017); doi: 10.1117/12.2262339
Show Author Affiliations
Yuzhen Lu, Michigan State Univ. (United States)
Renfu Lu, Agricultural Research Service (United States)
Michigan State Univ. (United States)


Published in SPIE Proceedings Vol. 10217:
Sensing for Agriculture and Food Quality and Safety IX
Moon S. Kim; Kuanglin Chao; Bryan A. Chin; Byoung-Kwan Cho, Editor(s)

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