Full-surface defect detection of navel orange based on hyperspectral online sorting technology.

Abstract

The whole-surface hyperspectral image acquisition of navel orange is particularly important for surface defect detection and quality classification. Because the light intensity at the edge of the navel orange is lower than that in the middle, the defects on the surface of the navel orange cannot be effectively identified. In this paper, a hyperspectral online sorting device for the whole-surface defects of navel orange is proposed. First of all, the image data of navel orange is collected by online detection sorting equipment and the spectral image of the characteristic wave peak of 1655.72nm was extracted. Then, the light intensity at the edge of the navel orange is enhanced by nonuniformity correction based on quadratic curve fitting, and the light intensity correction of the navel orange is realized. Finally, the corrected image is segmented by the threshold to obtain surface defects, and the number of surface defect pixels is improved effectively compared with that before light intensity correction. Ultimately, the online sorting test is carried out, and the detection accuracy is 100%. This indicates that this method effectively improves the sensitivity of defect detection. At the same time, the dimensionality reduction of hyperspectral data is also carried out, which is conducive to improving the efficiency of online detection.