The present application relates to the technical field of disaster detection, in particular to a
geological disaster detection method and
system based on
image processing, comprising the following steps: collecting multi-temporal topographic images and dividing them into blocks, constructing a main boundary angle difference value array, calculating the included angle change to screen image blocks and combining fault regions, extracting crack contours to calculate the opening angle and construct the offset sequence, generating an enhanced feature map based on
gradient projection texture field interpolation, constructing a residual
data field to divide grid points, and determining abnormal regions. In the present application, the main boundary angle difference value array of the blocks is constructed and affine aggregation is performed in combination with the consistency of the edge gray gradient, so that the precise reconstruction and continuity
recovery of the cross-scale nonlinear fault structure in the topographic image are realized, the gradient derivative quantity is generated by using the crack endpoint opening angle offset sequence and the texture
vector field is expanded, which can sensitively capture the weak morphological changes of the local
topography in the
time evolution process, and solve the problem that the small disaster precursor features are difficult to identify in a complex background.