Abstract: This invention relates to improved sheet products and specifically to improved nonwoven sheet products made from highly oriented plexifilamentary film-fibril webs. The improved sheet products have high opacity and strength with a much wider range of porosity or Gurley Hill Porosity Values. In particular, sheet products made in accordance with the present invention have considerably higher Gurley Hill Porosity Values than similar weight sheet products subject to the same finishing treatments in accordance with prior known sheet materials. Similarly, sheet products made in accordance with the present invention can be made which have much lower Gurley Hill Porosity Values than prior sheet materials. The invention includes numerous methods and data characterizing the webs and sheets that form the improved sheet materials.

Abstract: This invention relates to improved sheet products and specifically to improved nonwoven sheet products made from highly oriented plexifilamentary film-fibril webs. The improved sheet products have high opacity and strength with a much wider range of porosity or Gurley Hill Porosity Values. In particular, sheet products made in accordance with the present invention have considerably higher Gurley Hill Porosity Values than similar weight sheet products subject to the same finishing treatments in accordance with prior known sheet materials. Similarly, sheet products made in accordance with the present invention can be made which have much lower Gurley Hill Porosity Values than prior sheet materials. The invention includes numerous methods and data characterizing the webs and sheets that form the improved sheet materials.

Abstract: The present invention relates to a parallel processing image analysis method and system for identifying objects in a background by generating a description, which may be either a histogram or co-occurrence matrix, of the gray level space of the image by using an entropic kernel to recursively analyze the gray level space for candidate objects and validating the presence of valid objects by comparing the candidate object attribute values to a defined set of valid object attribute values contained in a driver. The method may be used in a wide variety of industrial inspection techniques, including colony counting and the identification of discrete features in carpets and of pigment elements embedded in a polymer.

Abstract: Accessing the exterior points of an object is used in the area of object identification when it is important to use the information in the local exterior environment of an object in order to extract a feature which may be useful for object recognition. Examples of this type of feature which are important for recognizing and classifying objects occur in the area if bacterial detection. Adaptive classification is a way of making the analysis independent of variations in imaging conditions, such as lighting, positioning, electronic amplification, etc. Two general methods can be used to access the local exterior environment of an object, knowing the perimeter points of the object. In the first method, the shape of an annular exterior region around the object of interest can be made to follow the shape of the object itself. In the second method, an known exterior shape, such as a circle, is used to characterize the exterior contour region, approximating the shape of the object.

Abstract: The present invention relates to image analysis methods and systems for identifying objects in a background by generating a description, which may be either a histogram or co-occurrence matrix, of the gray level space of the image by using an entropic kernel to recursively analyze the gray level space for candidate objects and validating the presence of valid objects by comparing the candidate object attribute values to a defined set of valid object attribute values contained in a driver. The present invention includes recursive, iterative and parallel processing methods. The methods may be used in a wide variety of industrial inspection techniques, including colony counting and the identification of discrete features in carpets and of pigment elements embedded in a polymer.

Abstract: The present invention relates to a digital image analysis method for automatically identifying an object in a background, characterizing the object by color by determining at least one interior point of the object, and displaying the object on a monitor in color corresponding to the natural color of the object and a digital image analysis method for displaying an object on a monitor in color. The methods are adaptive in that they create a new pallette for each image being processed. The system used to implement the methods is cost effective in that a black-and-white image processing board can be used in conjunction with a color filter and a color monitor.

Abstract: A method for determining the quality of dispersion of glass fibers in a thermoplastic resin preform layer compares the mean characteristic length of the glass fiber bundles in the preform layer to a predetermined value indicative of dispersion of the glass fibers. The thermoplastic resin preform layer characterized by this method comprises a plurality of individual glass fibers and some degree of undispersed glass fiber bundles intimately mixed with a plurality of discrete thermoplastic fibers. The glass fibers are introduced to the mixture having a length of about 1 cm. to about 8 cm. After mixing, some of the glass fiber bundles break up, and some residual glass fiber bundles remain. A preform layer which has acceptable dispersion has residual glass fiber bundles having a mean apparent length of less about 1.365 mm.

Abstract: The present invention relates to a method of identifying and characterizing, by color, at least one valid object having at least one predetermined attribute value in a background. The method generates a plurality of images of a candidate object and the background, where each image is one of three primary color images or a black-and-white image. The method searches the image for a candidate object using an automatically calculated threshold gray level and determines the interior points of the candidate object. The method further determines the gray level value of the interior points in the image and calculates a color parameter for the interior points. The method thus enables one to characterize the candidate object by the color parameter and validate the candidate object having the valid object predetermined attribute value.

Abstract: The present invention relates to an image analysis method for determining the interior points of an object in a background when the contour, or perimeter points, of the object are known. By accessing the interior points of an object, textural and color information can be derived, thereby allowing for object recognition. Further, the ability to determine interior points of an object allows for complete identification of all objects in an image. By determining the interior points, one may "blacken out", or effectively remove previously identified objects from an image, creating a remainder image for further searching.

Abstract: The present invention relates broadly to a method of image analysis for analyzing the texture of a surface, and to a saxony-type carpet having a tightly tailored surface texture characterized by this method. The method employs a model based on a second order co-occurrence matrix model which calculates a set of textural parameters for image classification. This co-occurrence matrix model examines the statistics of the spatial relationship between gray levels in a homogeneously textured image with calculated textural features which represent measures such as homogeneity and contrast. The method of the present invention uses this model to construct a set of normalized textural parameters from the textural parameters and calculates a value for the normalized textural parameters from this set, where the normalized textural parameters are related to the physical properties of the surface, such as pile lay of a carpet.