Combination of chemometric tools and image processing for bruise detection on apples
In this paper, an experiment of using a hyperspectral imaging system for bruise detection on Golden Delicious apples is reported. The hyperspectral imaging system was built in the wavelength region between 400 and 1000nm. Chemometric tools such as PCA and PLSDA were used to extract and summarize the spectral information from the hyperspectral images. Image processing methods made it possible to segment the region-of-interest according to the spatial features. Classification algorithms based on PCA and PLSDA results were developed, respectively. Their performance with respect to the classification accuracy and feasibility to implement on-line sorting were compared. The chemometric tools are able to extract and summarize the pixel-based information, while the image processing methods provide region-based analysis to efficiently segment differences of the apple surface. This combination of image processing techniques and chemometric tools provides a very promising approach for studying the quality of apples.
image processing pca plsda multispectral imaging