A novel quasi-contact lens auto-inspection system

This article describes a novel inspection system that uses machine vision to detect optical defects in quasi-contact lenses. The hardware consists of a host computer, a die float, and an interferometer that produces grating moiré fringe pattern images of the quasi-contact lenses being inspected. The major optical region of the lens image is first segmented, and then the middle axes of each fringe on the optical region are determined. Three characteristic features of the fringe, namely, the degree of twist, parallelism, and orthogonality, are extracted to create an effective mapping of the original features to a semantic description of the textures. Finally, the quality of the quasi-contact lens is determined using a control chart procedure. A set of 147 quasi-contact lens images was used to validate the proposed system. The successful detection rate was 95.3%, demonstrating that the proposed algorithm is a feasible solution for detecting optical defects on the quasi-contact lenses.