Donald B. Curtis - Highland UT, US Shawn Reid - Orem UT, US
Assignee:
The Generations Network, Inc. - Provo UT
International Classification:
G06K 9/00
US Classification:
382181
Abstract:
A method of processing an image includes receiving a digital version of the image, processing the digital version of the image through at least two binarization processes to thereby create a first binarization and a second binarization, and processing the first binarization through a first optical character recognition process to thereby create a first OCR output file. Processing the first binarization through a first optical character recognition process includes compiling first metrics associated with the first OCR output file. The method also includes processing the second binarization through the first optical character recognition process to thereby create a second OCR output file. Processing the second binarization through the first optical character recognition process includes compiling second metrics associated with the second OCR output file. The method also includes using the metrics, at least in part, to select a final OCR output file from among the OCR output files.
Dual Sided Mirror Book Imaging Devices And Methods
Jack Reese - Lindon UT, US Shawn Reid - Orem UT, US
Assignee:
Ancestry.com Operations Inc. - Provo UT
International Classification:
G02B 5/08
US Classification:
359866
Abstract:
Devices, systems, and methods for facilitating the imaging of books are presented. A first transparent plate and a second transparent plate may be positioned at approximately a 45 degree angle to the first transparent plate. A dual-sided mirror may be configured to be positioned substantially parallel with the first transparent plate and to be positioned substantially parallel with the second transparent plate. The first side of the dual-sided mirror may be configured to reflect a first image of a first page of a book, the first image being received by the dual-sided mirror through the first transparent plate. The second side of the dual-sided mirror may be configured to reflect a second image of a second page of the book, the second image being received by the dual-sided mirror through the second transparent plate.
Multi-Angle And Multi-Position Reprographic Copy Stand
Jack Reese - Lindon UT, US Shawn Reid - Orem UT, US
Assignee:
Ancestry.com Operations Inc. - Provo UT
International Classification:
A47B 23/00 B23P 11/00
US Classification:
248448, 29428
Abstract:
Various methods and devices involving reprographic copy stands are described. A reprographic copy stand may include a first support element configured to support a first cover of a book at a first plurality of angles. The reprographic copy stand may also include a second support element configured to support a second configured to support a second cover of the book at a second plurality of angles. The reprographic copy stand may include a platform configured to couple with the first support element at a first plurality of positions and the second support element at a second plurality of positions. The distance between the support elements may be variable according to the position of the first support selected from the first plurality of positions and the position of the second support selected from the second plurality of positions such that a plurality of book binding thicknesses are accommodated by the distance.
Multi-Perpendicular Line-Based Deskew With Affine And Perspective Distortion Correction
Jack Reese - Lindon UT, US Shawn Reid - Orem UT, US
Assignee:
Ancestry.com - Provo UT
International Classification:
G06K 9/32
US Classification:
382296
Abstract:
The present invention provides a method of correcting alignment of an image. The method includes identifying an image of a document, and detecting a plurality of lines within the image. The method also includes classifying at least a subset of the plurality of lines as either horizontal or vertical lines, and determining whether a variance exists within a subset of the plurality of lines. Furthermore, the method includes applying a corrective transformation to adjust the image, where the variance within the subset of the plurality of lines is at least partially reduced as compared to the variance prior to the application of the corrective transformation.
Automated Field Position Linking Of Indexed Data To Digital Images
Jack Reese - Lindon UT, US Shawn Reid - Orem UT, US Laryn Brown - Highland UT, US Randy Hansen - Lindon UT, US Mark Oswald - Cedar Hills UT, US
Assignee:
Ancestry.com - Provo UT
International Classification:
G06K 9/46
US Classification:
382190
Abstract:
According to one embodiment, a method of linking a document image with indexed data is provided. The method may be performed by providing a document image, which is a digitized document having various information. Indexed data is also provided, which is a record that includes information extracted from the document image or a different document image. The process is further performed by identifying a feature of the indexed data and analyzing the document image to determine whether the feature is present within the information of the digitized document. The feature may be information or a characteristic defined by the information extracted from the document image or the different document image. If the feature is present within the information of the digitized document, a determination is made that the indexed data corresponds with the document image and the indexed data is linked with the document image.
Clustering Historical Images Using A Convolutional Neural Net And Labeled Data Bootstrapping
- Lehi UT, US Michael Murdock - Lehi UT, US Jack Reese - Lindon UT, US Shawn Reid - Orem UT, US
Assignee:
Ancestry.com Operations Inc. - Lehi UT
International Classification:
G06K 9/62
Abstract:
Systems and methods for classifying historical images. A feature extractor may create feature vectors corresponding to a plurality of images. A first classification of the plurality of images may be performed based on the plurality of feature vectors, which may include assigning a label to each of the plurality of images and assigning a probability for each of the assigned labels. The assigned probability for each of the assigned labels may be related to a statistical confidence that a particular assigned label is correctly assigned to a particular image. A subset of the plurality of images may be displayed to a display device. An input corresponding to replacement of an incorrect label with a corrected label for a certain image may be received from a user. A second classification of the plurality of images based on the input from the user may be performed.
Clustering Historical Images Using A Convolutional Neural Net And Labeled Data Bootstrapping
- Lehi UT, US Michael Murdock - Lehi UT, US Jack Reese - Lindon UT, US Shawn Reid - Orem UT, US
Assignee:
Ancestry.com Operations Inc. - Lehi UT
International Classification:
G06K 9/62
Abstract:
Systems and methods for classifying historical images. A feature extractor may create feature vectors corresponding to a plurality of images. A first classification of the plurality of images may be performed based on the plurality of feature vectors, which may include assigning a label to each of the plurality of images and assigning a probability for each of the assigned labels. The assigned probability for each of the assigned labels may be related to a statistical confidence that a particular assigned label is correctly assigned to a particular image. A subset of the plurality of images may be displayed to a display device. An input corresponding to replacement of an incorrect label with a corrected label for a certain image may be received from a user. A second classification of the plurality of images based on the input from the user may be performed.
Clustering Historical Images Using A Convolutional Neural Net And Labeled Data Bootstrapping
- Lehi UT, US Michael Murdock - Lehi UT, US Jack Reese - Lindon UT, US Shawn Reid - Orem UT, US
Assignee:
Ancestry.com Operations Inc. - Lehi UT
International Classification:
G06K 9/62 G06K 9/46
Abstract:
Systems and methods for classifying historical images. A feature extractor may create feature vectors corresponding to a plurality of images. A first classification of the plurality of images may be performed based on the plurality of feature vectors, which may include assigning a label to each of the plurality of images and assigning a probability for each of the assigned labels. The assigned probability for each of the assigned labels may be related to a statistical confidence that a particular assigned label is correctly assigned to a particular image. A subset of the plurality of images may be displayed to a display device. An input corresponding to replacement of an incorrect label with a corrected label for a certain image may be received from a user. A second classification of the plurality of images based on the input from the user may be performed.
Perot Systems Government Services Jan 1999 - Feb 2003
Director of Development
Ancestry Jan 1999 - Feb 2003
Senior Director of Development
Wordperfect Jan 1989 - Jan 1999
Director of Development
Education:
Brigham Young University 1984 - 1987
Bachelors, Bachelor of Science, Computer Science, Mechanical Engineering
Skills:
Agile Methodologies Software Development Scrum Software Engineering Product Management C# Web Services User Experience Strategic Planning
mipig scored 24 points, one of four Titans in double figures, as Fullerton pulled away with a 34-5 run in the BracketBusters victory. Umipig made four of five three-point shots and the Titans (18-7) made all 12 of their free throws against the Bobcats (11-15), who were led by Shawn Reid with 20 points.