The invention relates to the technical field of
image segmentation, and discloses a jacquard fabric texture-oriented ultra-light UNet segmentation method and
system, and the method comprises the steps: receiving a to-be-segmented jacquard fabric texture image through an
encoder path, and carrying out the
feature extraction through employing a plurality of stages of encoders which are connected in sequence; the SCAB module performs optimization based on channel attention and space attention on the feature map output by each level of
encoder to obtain optimized features; the decoder path receives the feature pattern output by the last-stage
encoder and the optimization features of the corresponding levels, multiple levels of decoders which are connected in sequence are adopted for
feature transformation and up-sampling, and finally a segmentation result is output; the encoder and the decoder both adopt an LGB module, a convolutional layer or a PVMT module to perform
feature extraction, and the LGB module comprises
bottleneck convolution, a gating mechanism and channel attention; and the PVMT module comprises a plurality of Mamba models. According to the method, the characteristic extraction capability is maintained while the parameter quantity is reduced, and deep mixed characteristic representation of complex jacquard textures is realized.