The invention discloses a bionic visual image target recognition method fusing dot-line memory information, and the method comprises the steps of constructing a
grid cell set based on visual drive, constructing a distance
cell model, and calculating a displacement vector between the positions coded by a
grid cell group vector; calculating the response of all sensory neurons to each central concavepixel k through a
Gaussian kernel, wherein the response is used for target recognition; calculating the
fovea centralis of the current target image by using
Gaussian nuclear sensory cells, taking thefeature tag unit with the strongest response as the next jump point, and accumulating the corresponding stimulated identity cells; selecting a next-hop viewpoint, and updating a foveal displacement vector through a distance
cell model; and circularly repeating the calculation of the current position during the target identification process, selecting the next-hop viewpoint, and carrying out the vector calculation until the accumulation of a certain stimulated identity
cell reaches a threshold value 0.9, and considering the stimulated identity as the finally identified target. The method provided by the invention has a relatively higher recognition rate for the position change, zooming and shielded images.