Fig. 6: Application of the HyperspecI sensor for textile classification and apple bruise detection.
From: A broadband hyperspectral image sensor with high spatio-temporal resolution
a, The experiment configuration for the acquisition of fabric spectra. b, Measurements and reconstructed hyperspectral images of textile samples, together with synthesized RGB (sRGB) representations and exemplar hyperspectral images (1,220 nm, 1,320 nm and 1,480 nm for cotton fabrics and 1,320 nm, 1,420 nm and 1,600 nm for polyester fabrics). c, An SVM model for fabric classification based on spectral characteristics, achieving a high accuracy of 98.15% on the prediction set. d, The apple samples and experiment configuration. Apple samples with random bruises were constructed using the device shown on the right. e, The acquired measurement of apples and the corresponding spectral curves of bruised and normal portions. The characteristic wavelengths of apple bruises are distributed at 1,060 nm, 1,260 nm and 1,440 nm. f, Comparison of apple bruise detection between manual labelling (green bounding boxes) and model prediction (red bounding boxes). We used the pre-trained YOLOv5 network to detect bruised portions of apples. g, Quantitative results of apple bruise detection based on NIR and RGB images, respectively. a.u., arbitrary units.
