The invention relates to a
watermelon seed vigor grade classification method based on terahertz transmission and reflection
imaging data fusion. The method comprises the following steps: firstly, performing artificial
accelerated aging treatment on watermelon seeds under high-temperature and high-
humidity conditions to obtain samples with different activity grades; then, a terahertz time-domain
spectral imaging system is used for collecting transmission and reflection signals respectively, the transmission signals are subjected to color threshold segmentation to extract an
embryo region, and the reflection signals are subjected to Canny
edge detection and contour screening to extract a surface region; and after the obtained
signal is subjected to smooth filtering and
deconvolution processing, first-order derivative difference enhancement is further introduced, and a fusion spectrum is constructed by adopting a weighted fusion strategy. The fusion spectrum is subjected to
weight distribution through a frequency attention mechanism and then input to a feature
perception convolutional neural network, the network comprises two
layers of one-dimensional
convolution and nonlinear activation functions and is provided with high, medium and
low activity branch classification paths, and finally a
classification result of seed activity levels is output.