Abstract:
Techniques are described for forming microlens sheeting having composite images that appear to float with respect to the plane of the sheeting. As one example, a method comprises forming one or more images within a sheeting having a surface of microlenses, wherein at least one of the images is a partially complete image, and wherein each of the images is associated with a different one of the microlenses, wherein the microlenses have refractive surfaces that transmit light to positions within the sheeting to produce a plurality of composite images from the images formed within the sheeting so that each of the composite images appears to float with respect to the plane of the sheeting, and wherein forming the one or more images comprises forming the one or more images such that each of the composite images is associated with a different viewing angle range.
Abstract:
Techniques are described for forming microlens sheeting having composite images that appear to float with respect to the plane of the sheeting. As one example, a method comprises forming one or more images within a sheeting having a surface of microlenses, wherein at least one of the images is a partially complete image, and wherein each of the images is associated with a different one of the microlenses, wherein the microlenses have refractive surfaces that transmit light to positions within the sheeting to produce a plurality of composite images from the images formed within the sheeting so that each of the composite images appears to float with respect to the plane of the sheeting, and wherein forming the one or more images comprises forming the one or more images such that each of the composite images is associated with a different viewing angle range.
Abstract:
An apparatus to infer the resistivity of an electrode by stimulating the electrode with a capacitively coupled signal, and processing the resultant signal with circuitry that produces a signal having an amplitude that is a function of the resistivity of the electrode.
Abstract:
A computerized rating tool is described that assists a user in efficiently and consistently assigning expert ratings (i.e., labels) to a large collection of training images representing samples of a given product. The rating tool provides mechanisms for visualizing the training images in an intuitive and configurable fashion, including clustering and ordering the training images. In some embodiments, the rating tool provides an easy-to-use interface for exploring multiple types of defects represented in the data and efficiently assigning expert ratings. In other embodiments, the computer automatically assigns ratings (i.e., labels) to the individual clusters containing the large collection of digital images representing the samples. In addition, the computerized tool has capabilities ideal for labeling very large datasets, including the ability to automatically identify and select a most relevant subset of the images for a defect and to automatically propagate labels from this subset to the remaining images without requiring further user interaction.