Visual detection of apple bruises using AdaBoost algorithm and hyperspectral imaging

Figures & data

Figure 1. RGB and grayscale images at 811 nm of intact and bruise apples.

Figure 2. Hyperspectral reflectance imaging system and hyperspectral image structure schematic diagram.

Figure 3. The initial and pretreated spectra reflectance of intact and bruise apple at different time intervals after injury.

Table 1. Classification results based on full wavelengths and AdaBoost.

Data	Training Set					Test Set
	10min	1day	2day	3day	4day	10min	1day	2day	3day	4day
Initial data	80.56	90.28	94.44	94.44	93.06	80.56	91.67	94.44	97.22	97.22
Savitzky-Golay	86.11	88.89	95.83	97.22	97.22	86.11	94.44	94.44	97.22	97.22
2nd derivative	88.89	93.06	97.22	94.44	94.44	80.56	91.67	94.44	94.44	97.22
SNV	77.78	91.67	94.44	95.83	94.44	80.56	88.89	97.22	91.67	94.44
Mean center	83.33	95.83	98.61	98.61	93.06	86.11	94.44	97.22	100	100
MSC	95.83	94.44	98.61	98.61	98.61	97.22	100	100	100	100

Figure 4. The confusion matrix for the training results of the initial data.

Table 2. The results of CFS procedure performed on Initial data and preprocessed data.

Data	Numbers	Selected bands based on CFS algorithm
Initial data	4	45, 118, 119, 123
Savitzky-Golay	9	30, 46, 92, 119, 121, 122, 123, 124, 125
2nd derivative	10	11, 13, 15, 47, 48, 81, 89, 98, 99, 100
SNV	8	1, 83, 84, 87, 88, 89, 96, 125
Mean center	4	1, 26, 54, 118
MSC	8	1, 51, 82, 92, 93, 115, 117, 124

Table 3. Classification results based on selected wavelengths and AdaBoost.

Data	Training Set					Test Set
	1min	1day	2day	3day	4day	1min	1day	2day	3day	4day
Initial data	90.28	87.5	95.83	98.61	98.61	83.33	94.44	97.22	97.22	97.22
Savitzky-Golay	90.28	91.67	98.61	95.83	98.61	86.11	97.22	97.22	100	97.22
2^nd derivative	86.11	91.67	95.83	93.06	94.44	83.33	91.67	88.89	86.11	97.22
SNV	86.11	91.67	95.83	98.61	95.83	91.67	91.67	100	91.67	94.44
Mean center	84.72	94.44	95.83	98.61	93.06	86.11	97.22	91.67	100	100
MSC	93.06	94.44	98.61	98.61	97.22	97.22	97.22	100	100	100

Figure 5. ICA transform results of the bruise apples’ hyperspectral images based on the full and characteristic wavelengths. (a) The first four component images of ICA transform based on full wavelengths.(b) The first four component images of ICA transform based on characteristic wavelengths

Figure 6. Flow chart of apple bruise region detection algorithm.

Table 4. Detection results of apple slight bruise by image recognition.

Type	Number	Correct	Incorrect	Accuracy/%
Intact	54	52	2	96.30
Bruise 1 min	54	47	7	87.04
Bruise 1 day	54	50	4	92.59
Bruise 2 day	54	52	2	96.30
Bruise 3 day	54	53	1	98.15
Bruise 4 day	54	53	1	98.15
Total	324	307	17	94.75