The Algorithm of Descriptor Based on Locality Preserving Projections

This paper presents a novel algorithm to design the descriptor of image feature points based on locality preserving projections(LPP).Firstly,an eigenmatrix was pre-produced by LPP,and a high-dimensional gradient vector was constructed by the gradient vectors of all neighborhood points around feature points.Then,the high-dimensional gradient vector was embed- ded into a lower dimensional manifold space with the eigenma- trix,and a low-dimensional descriptor of the feature points was generated.The proposed algorithm can preserve invariability on the geometric structure:the eigenvectors which are neighboring each other in the original space will maintain the same attribute in low-dimensional space;on the contrary,the unsimilar eigen- vectors become apart farther each other.Therefore,the descrip- tion generated by our algorithm can show the interrelationship between features and has strong robustness.Moreover,the com- parative experiments illustrated that the proposed algorithm is more rapid and accurate than SIFT and PCA-SIFT.