US 11,954,932 B2
Systems and methods for automatic detection of features on a sheet
Jae Min Lee, Fullerton, CA (US); and Joseph W. Wezorek, Pasadena, CA (US)
Assigned to Bluebeam, Inc., Pasadena, CA (US)
Filed by Bluebeam, Inc., Pasadena, CA (US)
Filed on Feb. 16, 2021, as Appl. No. 17/177,072.
Claims priority of provisional application 63/093,031, filed on Oct. 16, 2020.
Prior Publication US 2022/0121844 A1, Apr. 21, 2022
Int. Cl. G06V 30/414 (2022.01); G06F 18/22 (2023.01); G06F 40/279 (2020.01); G06N 20/00 (2019.01); G06V 10/10 (2022.01)
CPC G06V 30/414 (2022.01) [G06F 18/22 (2023.01); G06F 40/279 (2020.01); G06N 20/00 (2019.01); G06V 10/10 (2022.01); G06V 10/16 (2022.01)] 17 Claims
OG exemplary drawing
 
1. A computer-implemented method for detecting a target object on a document page, the method comprising:
detecting a sample target area on a sample document page by detecting (i) a line within a predetermined distance from at least one of a first terminal side or a second terminal side of the sample document page and (ii) one or more textual characters positioned adjacent to the line, wherein the predetermined distance corresponds to a ratio of a total surface area of the sample document page;
generating an image by overlapping a plurality of sample document pages with one another;
detecting one or more cells within the sample target area on the image, wherein the sample target area includes a sample target object;
extracting one or more informational features from each of the one or more cells, wherein the one or more informational features define characteristics of a corresponding cell of the one or more cells;
training a machine learning model, using the one or more informational features extracted from each of the one or more cells, to detect the sample target object; and
detecting the target object on the document page using the trained machine learning model.