A high-precision vision measurement method based on dimension characteristics of sequential partial images

Due to the advantages of continuity, non-contact and non-destructiveness, vision measurement has become an innovative method in dimension measurement. To realize the high-precision vision measurement for large scale machine parts, a new vision measurement method based on dimension characteristics of sequential partial images is proposed. To overcome the corresponding problems arising from the relative rotation between two sequential partial images, a rectifying method based on texture features is used at the first step. Then, the transitional distribution modality of part image edges and its effects on measurement precision are analyzed. To get rid of the effects, a method of edge-pixel compensation is put forward, which availably improve measurement precision. Finally, a case study is provided to demonstrate the analysis procedures and effectiveness of the proposed methodology. The experiments show that the relative error is less than 0.012% using the sequential image measurement method to gauge large scale straight-edge parts. The measurement precision meets the need of the precise measurement .