In order to provide important basis for case analysis in the field of criminal investigation

based on footprint analysis technology

aiming at footprint image data

Relation Network is used to realize bare footprint recognition.Firstly

based on the Otsu algorithm and the similarity between left and right foot

image denoising and data augmentation are carried out respectively.Then

the image is trained in Relation Network.The training set included bare footprint data of 63 objects.And the data of another 50 objects is used as the test set.Finally

the recognition rate of the models under four training methods are compared and analyzed.In the training of Relation Network

including multi-task training

four training methods are adopted respectively.Experiments show that the multi-task method based on autoencoder and multi-task learning is the best of all the training methods

and the recognition rates on left and right footprints are 88.5 % and 88.3 %

respectively.