A Rotation-invariant Texture Retrieval Algorithm Based on Parameterless Statistical Features

We analyze the spectrum influence between Radon transform and Log-polar transform when rotation effect is eliminated.The average retrieval performance of wavelet and NSCT with different retrieval parameters is also studied.Based on which,we design a multi-scale and multi-orientation texture transform spectrum,as well as rotation-invariant feature vector and its measurement criteria.Then a new two-level rotation-invariant texture retrieval algorithm based on no-parameter statistic features is proposed.The experimental results on Brodatz image database show that our algorithm is appropriate for main orientation capturing and detail information description.The combination of this two-level progressive retrieval strategy and multi-scale analysis method can effectively improve retrieval efficiency,compared with traditional algorithms,and ensure a high precision as well.