Quantitative defects detection has always been the one of the difficulties in optical element surface quality evaluation. In order to solve this problem, the optical element surface defects detection based on dark-field imaging system, which has been researched by our group team for nearly twenty years, has been summarized. The plane and sphere optical element surface defects detection details are introduced. Specifically, it involves plane optical element surface leveling, sphere optical element spherical center alignment, low magnification image acquisition, low magnification image stitching, feature extraction, high magnification defects detection and report output based on the form of specific standard (Such as America Military Standard MIL-PRF-13830B or China National Standard GB/T 1185-2006). Besides, a China National Standard about digitized quantitative measurement of the defect, which is proposed by our group (now is in the stage of request for public advice), is also introduced.
A method to simulate and design the dark-field imaging scene for optical spherical surface imperfection is proposed based on raytracing. Rays emit from the finite aperture camera model to the world space, split at the optical surface and finally obtain luminance from light sources. Thus the image function can be solved by raytracing and Monte Carlo integration of luminous flux. A typical dark-field imaging scene is presented, of which realistic images of various kinds of lens are rendered. The simulated images can well predict where the spots of light source locate and reveal imperfections. At last, corresponding adjustments are implemented to eliminate the influence of second surface.
Surface defect detection is one of the essential steps of quality control. However, it is hard to illuminate defects on curved surface, as the surface properties and geometrical shapes lead to uneven background light distribution on the captured image. In this paper, all the devices used by machine vision including the sample are regarded as part of the whole illuminating scene. Models for each component of the illuminating scene are established separately and Monte Carlo ray tracing is used for generating the image. At last, a specific illuminating scene is designed for illuminating a part of curved cylinder surface. the entire surface is lightened and the non-uniform image caused by background light is greatly improved. The paper analyses how the components of illuminating scene, such as light source placement, surface properties, influence the grayscale distribution on image background and provides method to design illuminating scene for real-time accurate curved surface defect detection.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.