Selection of optimal bands for developing multispectral system for inspecting apples for defects

I. Baek; C. Eggleton; S. A. Gadsden; M. S. Kim

doi:10.1117/12.2520469

30 April 2019 Selection of optimal bands for developing multispectral system for inspecting apples for defects

I. Baek, C. Eggleton, S. A. Gadsden, M. S. Kim

Proceedings Volume 11016, Sensing for Agriculture and Food Quality and Safety XI; 110160F (2019) https://doi.org/10.1117/12.2520469
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

Hyperspectral image technology is a powerful tool, but oftentimes the data dimension of hyperspectral images must be reduced for practical purposes, depending on the target and environment. For detecting defects on a variety of apple cultivars, this study used hyperspectral data spanning the visible (400 nm) to near-infrared (1000 nm). This paper presents the preliminary results from the selection of optimal spectral bands within that region, using a sequential feature selection method. The selected bands are used for multispectral detection of apple defects by a classification model developed using support vector machine (SVM). As a result, five optimal wavelengths were selected as key features. When using optimal wavelengths, the accuracy of the SVM and SVM with RBF kernel achieved accuracies over 90% for both the calibration and validation data set. However, the results of SVM with RBF kernel (>80%) based on image was more robust than SVM model (>50%). Moreover, SVM with RBF model classified between bruise and sound regions as well specular. The result from this study showed the feasibility of developing a rapid multispectral imaging system based on key wavelengths.

Citation Download Citation

I. Baek, C. Eggleton, S. A. Gadsden, and M. S. Kim "Selection of optimal bands for developing multispectral system for inspecting apples for defects", Proc. SPIE 11016, Sensing for Agriculture and Food Quality and Safety XI, 110160F (30 April 2019); https://doi.org/10.1117/12.2520469

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