The present application belongs to the technical field of
image analysis, and particularly relates to a kind of egg oiling quality detection method based on
machine vision, to solve the technical problems of
low contrast, high light interference and single information dimension faced by traditional
machine vision in prior art, comprising the following steps: S1, obtaining the multispectral polarized image of the egg to be detected;S2, obtaining the contour
mask and highlight area
mask of the egg;S3, obtaining the effective analysis area;S4, generating a
linear polarization degree feature map representing
oil film uniformity;S5, generating a
spectral angle feature map representing oiling thickness;S6, constructing a region graph with each superpixel as a node and an adjacency relationship as an edge;S7, fusing the initial
feature vector of the superpixel node;S8, identifying and outputting the superpixel node determined as an oiling defect;S9, comprehensively evaluating the oiling quality grade of the egg. The automatic, high-precision comprehensive grading of egg oiling quality is realized.