Determination of bruised potatoes by GLCM based on hyperspectral imaging technique

A texture recognition method based on hyperspectral imaging technology was proposed for the difficulty in bruise detection of potatoes. Firstly, the hyperspectral images of healthy and bruised potatoes were collected, and then they were used to generate principal component images by using peA method. To enhance the features of bruised region in these principal component images, the histogram equalization, mean smoothing, and gradient method were used, respectively, which proved that the histogram equalization method was the most suitable. Extra, through the selection of parameters of gray level co-occurrence matrix (gray level L and distance D), the best prediction results were obtained when L=8 and D=8. Finally, SA method was applied to reduce the dimension of the texture data, and the recognition rate reached 93.75%.