E.i. Dupont De Nemours and Company

Akhileswar G Vaidyanathan

Michael J Merrill

James Arthur Whitcomb

Hyun Sung Lim

Michael Patrick Milone

Ralph A Franke

Dennis B Fowler

R Gail Raty

Warren Francis Knoff

Gregory Paul Weeks

Larry Ray Marshall

James Edmond Van Trump

Barry Rubin

Wade Thomas Rogers

Aaron J Owens

Theresa Ann Weston

Allan Robert Moser

Karen Marie Bloch

Robert G Pembleton

Herbert Alan Holyst

Hooshmand M Kalayeh

Mark Joseph Tribo

David Reuben Argentar

A method of discovering one or more patterns in two sequences of symbols Sand Sincludes the formation, for each sequence, of a master offset table that groups for each symbol the position in the sequence occupied by each occurrence of that symbol. The difference in position between each occurrence of a symbol in one of the sequences and each occurrence of that same symbol in the other sequence is determined and a Pattern Map is formed. For each given value of a difference in position the Pattern Map lists the position in the first sequence of each symbol therein that appears in the second sequence at that difference in position. The collection of the symbols tabulated for each value of difference in position thereby defines a parent pattern in the first sequence that is repeated in the second sequence. A computer readable medium having instructions for controlling a computer system to perform the method and a computer readable medium containing a data structure used in the practice of the method are also disclosed.

Method of discovering patterns in symbol sequences

A distributed hierarchical evolutionary modeling and visualization of empirical data method and machine readable storage medium for creating an empirical modeling system based upon previously acquired data. The data represents inputs to the systems and corresponding outputs from the system. The method and machine readable storage medium utilize an entropy function based upon information theory and the principles of thermodynamics to accurately predict system outputs from subsequently acquired inputs. The method and machine readable storage medium identify the most information-rich (i.e., optimum) representation of a data set in order to reveal the underlying order, or structure, of what appears to be a disordered system. Evolutionary programming is one method utilized for identifying the optimum representation of data.

Distributed hierarchical evolutionary modeling and visualization of empirical data

A method of texturing fluoropolymer film and the textured product produced, which product retains the texture imparted after further processing, such as in thermoforming or molding processes.

Process of preparing textured fluoropolymer films

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.

Nonwoven sheet products made from plexifilamentary film fibril webs

When identifying an object in an image, very often redundant identifications of the object may occur. The present invention relates to methods of image analysis for resolving such redundant identifications of an object. More specifically, the present invention relates to object identification schemes which obtain multiple representations of the same object. In addition, such identification schemes may identify void, or donut-shaped objects when a single search, or multiples searches, of the image are performed. Further, the present invention is useful in resolving several distinct objects where other identification schemes employing either single or multiple searching have identified these distinct objects as a single clumped object. The present invention may be used, for instance, to determine whether a smaller object is contained within another, larger object.

Method for resolving redundant identifications of an object

Image analysis methods and systems are used for identifying objects in a background by defining a data space, such as a histogram or a color space. The data space comprises a plurality of sub-spaces, which could be selected based, for example, on a histogram, or on the way pixel values or color parameters cluster in their respective spaces. The threshold values in the data space are selected, a list of all ordered pairs of thresholds is generated to define multiple data sub-spaces, and the image is multiply searched, once in each sub-space for at least one representation of a candidate object, where the candidate object has at least one predetermined attribute value. Valid objects are identified by comparing the candidate object attribute values to a defined set of valid object attribute values contained in a driver.

Adaptive vision system using dual thresholding

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.

Iterative method and system of identifying valid objects in a background

The present invention relates to an image analysis method and system for identifying objects in a background by generating a description, which in this case is a 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.

Method and system of identifying a valid object in a background of an

The present invention relates to an image analysis method and system for separately identifying each clumped homogeneous object in an image. The image includes at least one clump of homogeneous objects and at least one isolated homogeneous object. This image analysis method may be used in 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.

Method and system of separately identifying clumped homogeneous objects

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.

Parallel processing method and system for identifying valid objects in a

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.

Methods for determining the exterior points of an object in a background

Adaptive vision system

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.

Adaptive display system

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.

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Hockessin, DE, United States of America

Akhileswar G Vaidyanathan