Multiscale Recognition Algorithm for Eye Ground Texture Based on Fusion Threshold Equalization

Abstract

The eye ground texture is disturbed by non ideal imaging factor such as noise, it will affect the clinical diagnosis in practice, an improved multi scale retina eye ground texture recognition algorithm is proposed based on fusion area threshold. The nonlinear sampling multi-scale transform is used to analyze the geometric space coefficient of retinal vessels with multi direction and shift invariant features, the regional threshold filtering is integrated, it is used to suppress the effect of non-uniform blocks for texture recognition. The maximum likelihood local mean standard deviation analysis is used for texture parameters estimation and recognition. The noise reduced greatly, accurate identification of texture feature is obtained. Simulation results show that the algorithm can well characterize the retinal vascular texture, it has good performance in different texture feature recognition, the recognition accuracy is improved, and it has good robustness.