The invention relates to the technical field of garbage classification, in particular to an intelligent kitchen garbage classification
system based on
the Internet of Things, which comprises a node access module, an image preprocessing module, an
edge structure judgment module, an oil-water proportion sensing module and a garbage type classification module. According to the method, effective binding of node states is realized through combination of node geographic identifiers and timestamps, the spatial
traceability precision of garbage throwing behaviors is improved, the physical identification accuracy of garbage components in the image is enhanced through linkage of image gray difference extraction and spectral
reflectivity calculation, direction features are constructed through gradient amplitudes of edge regions, and the spatial
traceability precision of the garbage throwing behaviors is improved. The target stability of edge features in the image is enhanced by combining a texture consistency screening mechanism of a continuous region, and spectrum inversion
processing of oil and water distribution in the image is completed through
grease feature peak matching and
moisture index threshold extraction; and the imaging recognition capability of typical components of the kitchen waste is improved, and the reliability of kitchen waste image recognition and the
automation level of the classification process are enhanced.