Image retrieval based on variable k-nearest neighbor locally linear embedding data dimension reduction algorithm
Mianshu Chen · Journal of Jilin University · 2008
In content based image retrieval,computation complexity will increase seriously as the demension of the image feature increases.When reducing the vector dimension with locally linear embedding algorithm,the number k of nearest neighbors should be determined.In this paper we propose a variable k neighbors LLE(VK-LLE) method based on the distribution of the image feature.The VK-LLE method can reduce the vectors dimension with keeping their original topology structure into a lower dimension space.Experiment shows that the proposed VK-LLE method can achieve higher precision rate in content based image retrieval problem.