Patents by Inventor Jose Alberto Pablo Andreotti

Jose Alberto Pablo Andreotti has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Preprocessing images for OCR using character pixel height estimation and cycle generative adversarial networks for better character recognition
    Patent number: 11836969
    Abstract: A text extraction computing method that comprises calculating an estimated character pixel height of text from a digital image. The method may scale the digital image using the estimated character pixel height and a preferred character pixel height. The method may binarizes the digital image. The method may remove distortions using a neural network trained by a cycle GAN on a set of source text images and a set of clean text images. The set of source text images and clean text images are unpaired. The source text images may be distorted images of text. Calculating the estimated character pixel height may include summarizing the rows of pixels into a horizontal projection, and determining a line-repetition period from the projection, and quantifying the portion of the line-repetition period that corresponds to the text as the estimated character pixel height. The method may extract characters from the digital image using OCR.
    Type: Grant
    Filed: September 24, 2021
    Date of Patent: December 5, 2023
    Assignee: John Snow Labs Inc.
    Inventors: Jose Alberto Pablo Andreotti, David Talby
  • PREPROCESSING IMAGES FOR OCR USING CHARACTER PIXEL HEIGHT ESTIMATION AND CYCLE GENERATIVE ADVERSARIAL NETWORKS FOR BETTER CHARACTER RECOGNITION
    Publication number: 20220012522
    Abstract: A text extraction computing method that comprises calculating an estimated character pixel height of text from a digital image. The method may scale the digital image using the estimated character pixel height and a preferred character pixel height. The method may binarizes the digital image. The method may remove distortions using a neural network trained by a cycle GAN on a set of source text images and a set of clean text images. The set of source text images and clean text images are unpaired. The source text images may be distorted images of text. Calculating the estimated character pixel height may include summarizing the rows of pixels into a horizontal projection, and determining a line-repetition period from the projection, and quantifying the portion of the line-repetition period that corresponds to the text as the estimated character pixel height. The method may extract characters from the digital image using OCR.
    Type: Application
    Filed: September 24, 2021
    Publication date: January 13, 2022
    Applicant: John Snow Labs Inc.
    Inventors: Jose Alberto Pablo Andreotti, David Talby
  • Preprocessing images for OCR using character pixel height estimation and cycle generative adversarial networks for better character recognition
    Patent number: 11176410
    Abstract: A text extraction computing method that comprises calculating an estimated character pixel height of text from a digital image. The method may scale the digital image using the estimated character pixel height and a preferred character pixel height. The method may binarizes the digital image. The method may remove distortions using a neural network trained by a cycle GAN on a set of source text images and a set of clean text images. The set of source text images and clean text images are unpaired. The source text images may be distorted images of text. Calculating the estimated character pixel height may include summarizing the rows of pixels into a horizontal projection, and determining a line-repetition period from the projection, and quantifying the portion of the line-repetition period that corresponds to the text as the estimated character pixel height. The method may extract characters from the digital image using OCR.
    Type: Grant
    Filed: October 27, 2019
    Date of Patent: November 16, 2021
    Assignee: John Snow Labs Inc.
    Inventors: Jose Alberto Pablo Andreotti, David Talby
  • PREPROCESSING IMAGES FOR OCR USING CHARACTER PIXEL HEIGHT ESTIMATION AND CYCLE GENERATIVE ADVERSARIAL NETWORKS FOR BETTER CHARACTER RECOGNITION
    Publication number: 20210124979
    Abstract: A text extraction computing method that comprises calculating an estimated character pixel height of text from a digital image. The method may scale the digital image using the estimated character pixel height and a preferred character pixel height. The method may binarizes the digital image. The method may remove distortions using a neural network trained by a cycle GAN on a set of source text images and a set of clean text images. The set of source text images and clean text images are unpaired. The source text images may be distorted images of text. Calculating the estimated character pixel height may include summarizing the rows of pixels into a horizontal projection, and determining a line-repetition period from the projection, and quantifying the portion of the line-repetition period that corresponds to the text as the estimated character pixel height. The method may extract characters from the digital image using OCR.
    Type: Application
    Filed: October 27, 2019
    Publication date: April 29, 2021
    Applicant: John Snow Labs Inc.
    Inventors: Jose Alberto Pablo Andreotti, David Talby