基于三元组网络和混合粒子群的碎纸拼接算法OA北大核心CSTPCD

In order to solve the problems of low clustering accuracy and general splicing effect of heuristic algorithm after fine-grained cutting,an automatic splicing algorithm based on triplet network and hybrid particle swarm optimization was proposed.Splicing of shredded document could be divided into three stages:inter line clustering,compatibility evaluation and intra line splicing.First,in the inter row clustering stage,the projected image vectors were filled adaptively to supplement the missing feature information,and then the Gaussian mixture model clustering algorithm was used for clustering.After that,in the compatibility evaluation stage,with the help of the triplet network model,the clustered images of the same line were mapped to a common metric space,and a distance matrix with obvious discrimination was obtained.Finally,taking this distance matrix as the fitness value of particles,an intra line splicing algorithm based on hybrid particle swarm optimization was proposed.The experimental results show that the algorithm proposed can effectively improve the clustering accuracy and splicing accuracy,which has a good effect on the reconstruction of shredded paper.