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The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Patent No.:

US 11983944 B1

PDFFull Text
Date of Patent:
May. 14, 2024

Filed:

Feb. 27, 2023

Object detection and image cropping using a multi-detector approach

Applicant:

Kofax, Inc., Irvine, CA (US);

Inventors:

Jiyong Ma, San Diego, CA (US);

Stephen M. Thompson, Bonsall, CA (US);

Jan W. Amtrup, Silver Spring, MD (US);

Assignee:

KOFAX, INC., Irvine, CA (US);

Attorney:

Zilka-Kotab, P.C.

Primary Examiner:

Yosef Kassa

Int. Cl.
CPC ...
G06V 30/146 (2022.01); G06F 18/20 (2023.01); G06F 18/21 (2023.01); G06N 7/00 (2023.01); G06N 20/00 (2019.01); G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06T 7/12 (2017.01); G06T 7/13 (2017.01); G06T 7/194 (2017.01); G06T 7/70 (2017.01); G06T 7/90 (2017.01); G06V 10/44 (2022.01); G06V 10/762 (2022.01); G06V 10/80 (2022.01); G06V 20/40 (2022.01); G06V 30/162 (2022.01); G06V 30/18 (2022.01); G06V 30/19 (2022.01); G06V 30/413 (2022.01); G06V 10/28 (2022.01); G06V 30/10 (2022.01); G06V 30/224 (2022.01);
U.S. Cl.
CPC ...
G06V 30/147 (2022.01); G06F 18/217 (2023.01); G06F 18/285 (2023.01); G06N 7/00 (2013.01); G06N 20/00 (2019.01); G06T 7/0002 (2013.01); G06T 7/11 (2017.01); G06T 7/12 (2017.01); G06T 7/13 (2017.01); G06T 7/194 (2017.01); G06T 7/70 (2017.01); G06T 7/90 (2017.01); G06V 10/44 (2022.01); G06V 10/762 (2022.01); G06V 10/809 (2022.01); G06V 20/40 (2022.01); G06V 30/162 (2022.01); G06V 30/18105 (2022.01); G06V 30/19147 (2022.01); G06V 30/19173 (2022.01); G06V 30/413 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30176 (2013.01); G06V 10/28 (2022.01); G06V 30/10 (2022.01); G06V 30/2253 (2022.01);
Abstract

Computer-implemented methods for detecting objects within digital image data based on color transitions include: receiving or capturing a digital image depicting an object; sampling color information from a first plurality of pixels of the digital image, wherein each of the first plurality of pixels is located in a background region of the digital image; assigning each pixel a label of either foreground or background using an adaptive label learning process; binarizing the digital image based on the labels assigned to each pixel; detecting contour(s) within the binarized digital image; and defining edge(s) of the object based on the detected contour(s). Corresponding systems and computer program products configured to perform the inventive methods are also described.

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