Abstract: Embodiments pertain to methods of evaluating fiber quality by (1) receiving at least one in-line hologram image of the fiber; (2) reconstructing the in-line hologram image of the fiber into at least one three-dimensional image of the fiber that includes fiber-related data; and (3) correlating the fiber-related data to fiber quality. Such methods may also include: (4) adjusting fiber-related conditions; and (5) repeating steps 1-3 after the adjustment. Further embodiments pertain to systems for evaluating fiber quality in accordance with the aforementioned methods. Such systems may include a receiving area with a region for housing a fiber, a light source associated with the receiving area, a chamber associated with the light source and receiving area, a camera within the chamber, a processor in electrical communication with the camera, a storage device, an algorithm associated with the storage device and a graphical user interface (GUI) associated with the processor.

Abstract: Fabric wrinkles are automatically evaluated using a reliable, accurate, affordable, and efficient system. Two algorithms are used, the facet model algorithm and the plane-cutting algorithm, to extract features for evaluating wrinkles in fabrics. These algorithms eliminate the need for independent evaluation of a fabric specimen by a technician.

Abstract: A method for identification of anomalous structures, such as defects, includes the steps of providing a digital image and applying fractal encoding to identify a location of at least one anomalous portion of the image. The method does not require a reference image to identify the location of the anomalous portion. The method can further include the step of initializing an active contour based on the location information obtained from the fractal encoding step and deforming an active contour to enhance the boundary delineation of the anomalous portion.

Abstract: A cotton sample is subjected to noninvasive x-ray microtomographic image analysis in order to recognize cotton contaminants in the cotton sample. The cotton contaminants are detected and classified using an x-ray microtomographic system. Once the cotton contaminants in the cotton sample are detected and classified, the cotton sample may be graded based on the type and amount of cotton contaminants present.

Abstract: Fabric wrinkles are automatically evaluated using a reliable, accurate, affordable, and efficient system. Two algorithms are used, the facet model algorithm and the plane-cutting algorithm, to extract features for evaluating wrinkles in fabrics. These algorithms eliminate the need for independent evaluation of a fabric specimen by a technician.

Abstract: A method for identification of anomalous structures, such as defects, includes the steps of providing a digital image and applying fractal encoding to identify a location of at least one anomalous portion of the image. The method does not require a reference image to identify the location of the anomalous portion. The method can further include the step of initializing an active contour based on the location information obtained from the fractal encoding step and deforming an active contour to enhance the boundary delineation of the anomalous portion.

Abstract: A cotton sample is subjected to noninvasive x-ray microtomographic image analysis in order to recognize cotton contaminants in the cotton sample. The cotton contaminants are detected and classified using an x-ray microtomographic system. Once the cotton contaminants in the cotton sample are detected and classified, the cotton sample may be graded based on the type and amount of cotton contaminants present.

Abstract: A method and apparatus are provided by which a sheet-forming web may be characterized in four dimensions. Light images of the web are recorded at a point adjacent the initial stage of the web, for example, near the headbox in a paperforming operation. The images are digitized, and the resulting data is processed by novel algorithms to provide a four-dimensional measurement of the web. The measurements include two-dimensional spatial information, the intensity profile of the web, and the depth profile of the web. These measurements can be used to characterize the web, predict its properties and monitor production events, and to analyze and quantify headbox flow dynamics.

Abstract: Automatic detection of defects during the fabrication of semiconductor wafers is largely automated, but the classification of those defects is still performed manually by technicians. This invention includes novel digital image analysis techniques that generate unique feature vector descriptions of semiconductor defects as well as classifiers that use these descriptions to automatically categorize the defects into one of a set of pre-defined classes. Feature extraction techniques based on multiple-focus images, multiple-defect mask images, and segmented semiconductor wafer images are used to create unique feature-based descriptions of the semiconductor defects. These feature-based defect descriptions are subsequently classified by a defect classifier into categories that depend on defect characteristics and defect contextual information, that is, the semiconductor process layer(s) with which the defect comes in contact.

Abstract: A method for ultra-high resolution computed tomography imaging, comprising the steps of: focusing a high energy particle beam, for example x-rays or gamma-rays, onto a target object; acquiring a 2-dimensional projection data set representative of the target object; generating a corrected projection data set by applying a deconvolution algorithm, having an experimentally determined a transfer function, to the 2-dimensional data set; storing the corrected projection data set; incrementally rotating the target object through an angle of approximately 180°, and after each the incremental rotation, repeating the radiating, acquiring, generating and storing steps; and, after the rotating step, applying a cone-beam algorithm, for example a modified tomographic reconstruction algorithm, to the corrected projection data sets to generate a 3-dimensional image. The size of the spot focus of the beam is reduced to not greater than approximately 1 micron, and even to not greater than approximately 0.5 microns.

Abstract: A method for simultaneous transmission x-ray computed tomography (CT) and single photon emission tomography (SPECT) comprises the steps of: injecting a subject with a tracer compound tagged with a &ggr;-ray emitting nuclide; directing an x-ray source toward the subject; rotating the x-ray source around the subject; emitting x-rays during the rotating step; rotating a cadmium zinc telluride (CZT) two-sided detector on an opposite side of the subject from the source; simultaneously detecting the position and energy of each pulsed x-ray and each emitted &ggr;-ray captured by the CZT detector; recording data for each position and each energy of each the captured x-ray and &ggr;-ray; and, creating CT and SPECT images from the recorded data. The transmitted energy levels of the x-rays lower are biased lower than energy levels of the &ggr;-rays. The x-ray source is operated in a continuous mode. The method can be implemented at ambient temperatures.

Abstract: An apparatus and method for performing automated defect spatial signature alysis on a data set representing defect coordinates and wafer processing information includes categorizing data from the data set into a plurality of high level categories, classifying the categorized data contained in each high level category into user-labeled signature events, and correlating the categorized, classified signature events to a present or incipient anomalous process condition.