Valid measurement region segmentation method for the interferogram based on local fringe distribution features

Abstract

Oblique laser interferometry is an effective method to measure the form deviation of gear tooth flank. In the measurement, segmenting the valid measurement region (VMR) of the tooth flank from the captured interference fringe patterns (IFPs) is a crucial step that affects the measurement accuracy. To address the problem that current segmentation algorithms are susceptible to multiple forms of noise, making it difficult to guarantee their segmentation accuracy, this paper proposes a segmentation method that introduces the simulation tooth image (STI) as a template of the active shape model (ASM) to improve the segmentation accuracy. Firstly, an STI with a stable and noiseless fringe grayscale distribution was used to build the dataset and train, in order to obtain the initial contour of the tooth flank VMR. Next, the local grayscale features of the STI fringe were used to build a grayscale model of the initial contour, and the transformation parameters were adaptively calculated based on their a priori shape information. The trained segmentation model is searched in the IFPs to segment the tooth flank VMR. Finally, the proposed method was verified by comparing with segmentation methods based on grayscale and phase-shifting information. Moreover, this paper proves that the proposed method can be applied to the VMR recognition of IFPs of complex precision surfaces.