Common image edge detectors identify a mixture of image discontinuities caused by a local change of illumination,
texture or geometry. This document describes a method to separate depth-edges as a special instance of
geometry edges from all other edges in a single image, without a complicated sensor. A single color camera and
a red, green and blue light is used for scene illumination. Color shadows produced by the active illumination
provide discriminative features to detect depth-edges. Experimental results are used to demonstrate the discriminative
power of the proposed method and the performance of the depth-edge detection has been studied
analytically for different illumination conditions.
The accuracy of infrared temperature estimation can degrade significant for enclosed objects with reflective surfaces.
This paper describes a basic model of the incident radiation on a FPA sensor element considering a target
object, surrounding environment, surface temperatures, surface emissivity/reflection and optics. The model is
used to characterize the direct (one color method) temperature estimation error as a function of reflection, wavelength,
target temperatures and the environment geometry. Temperature estimation errors based on numerical
simulations with focus on near infrared are compared in this paper in a variety of scenarios assuming target
temperatures between 1000 to 1600 Kelvin. In one scenario is the measured radiation corrected to minimize the
error due to reflection.
This paper discusses scene-based estimation of non-uniformity correction (NUC) coefficients for focal-plane array sensors using spatial image neighborhood information (facet model). Several scene-based methods for estimation of non-uniformity correction (NUC) parameters were proposed in the literature, but artifacts can remain in specific situations. The objective of the work is to estimate non-uniformity correction coefficients using random scene images without making assumptions about motion or constant statistics. We show analytically and experimentally, how to reduce fixed pattern noise using a facet model. The method works best if out-of-focus images are available for calibration. We estimate NUC coefficients experimentally from a set of twelve scene images. The facet model approach can be an alternative for applications where artifacts otherwise would remain.
In our work, Tokyo Electron's iODP103 (integrated Optical Digital Profilometry) technology is used for integrated measurements on a next-generation Lithius Clean Track on after develop inspect (ADI) 300mm wafers. We show that single tool precision and tool-to-tool matching of three integrated systems fulfill the precision requirements of the 70nm DRAM technology node. Further results from a long-term pilot test using integrated scatterometry in a full-volume DRAM production of the 110nm technology node on 300mm wafers are also discussed. The data from our experiment is collected and charted in fab monitored statistical process control (SPC) charts, and compared to the charts from the POR CD-SEM measurements. The sampling plans are optimized in such a way as to perform fully integrated measurements on all wafers per lot, without throughput loss of the litho cluster. We demonstrate that the possibility of measuring all wafers per lot directly after development, in combination with the sensitivity of the method, allows the identification of effects that could not previously be identified by CD-SEM measurements alone.
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.