Abstract
Hyperspectral imaging system with the range of 450–990 nm was used to obtain the reflection spectral of star apples. The hyperspectral image data were used to identify skin defects such as insect bite, fungal infection, rusty spot and scarring of star apples. Principal component analysis (PCA) was used to reduce the spectral dimensionality of hyperspectral image data. Some specific PC images were evaluated visually for showing the difference between the skin defects in two spectral ranges including visible-near infrared and visible ranges. The results of this study can be used as the basis to develop algorithms for the classification of skin defects of star apple.
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