IP Library Granted Patent US 12,705,754
Granted Patent B2
US 12,705,754 · App. 18/202,633 · Granted Aug 11, 2026

Method, device, and computer program for detecting boundary of object in image

Inventor: Mahesh Babu A K (Noida, IN)
Assignee: SAMSUNG ELECTRONICS CO., LTD.
G06T7/13G06T7/162
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,705,754
App. No.
18/202,633
Filed
May 26, 2023
Granted
Aug 11, 2026
Kind
B2
Art Unit
2672
USPC
382/199
Abstract

The present disclosure provides a method of enabling image-based classification in real-time scenarios such as person presence identification, image-based gesture-recognition, real-time object detection, character recognition etc. The present disclosure provides a method and system of contour detection as part of data pre-processing pipeline for training and real-time inferencing of image-based multi-classifier using Machine Learning. A direction-based contour detection method is implemented as part of data pre-processing pipeline for real-time image-based multi-classifier/inferencing using ML algorithms. A parallelized contour detection method is implemented to reduce input feature set, reduce training and prediction time.

Claims (46)

1 . An electronic device comprising:

a memory storing instructions; and

at least one processor configured to execute the instructions to:

process an image to output a secondary image;

split the secondary image into a plurality of image segments;

scan the secondary image in a scan direction from a start pixel in each of the plurality of image segments to identify a first boundary pixel found as satisfying a boundary criteria during the scanning of the secondary image;

identify a second boundary pixel satisfying the boundary criteria by rotating the scan direction and scanning pixels in the secondary image along a circumferential direction centered on the first boundary pixel, wherein the scanning of the pixels starts from a pixel that is adjacent to the first boundary pixel, located in the rotated scan direction and adjacent to a direction opposite to the scan direction;

identify one or more next boundary pixels until a respective contour of an object is obtained in each of the plurality of image segments; and

obtain a complete contour of the object in the secondary image based on the respective contours obtained in the plurality of image segments,

wherein scan directions used for at least two different image segments are opposite to each other.

2 . The electronic device of claim 1 , wherein each pixel of the secondary image has a zero color value or non-zero color value, and the boundary criteria is satisfied when a corresponding pixel has the non-zero color value.

3 . The electronic device of claim 1 , wherein the scan direction corresponds to one or more of a west scan direction, an east scan direction, a north scan direction, or a south scan direction.

4 . The electronic device of claim 1 , wherein the start pixel is located at a middle of the secondary image.

5 . The electronic device of claim 1 , wherein the rotated scan direction is one or more of a west scan direction, an east scan direction, a north scan direction, a south scan direction, a north-west scan direction, a north-east scan direction, a south-west scan direction, or a south-east scan direction.

6 . The electronic device of claim 1 , wherein the start pixel is located at a left edge of the secondary image when the scan direction is an east direction, and an updated scan direction is a north-west direction or a south-west direction.

7 . The electronic device of claim 1 , wherein an angle between the rotated scan direction and its previous scan direction is equal to 135° or 225°.

8 . The electronic device of claim 1 , wherein the circumferential direction centered on the first boundary pixel is a clockwise or anticlockwise direction centered on the first boundary pixel.

9 . The electronic device of claim 1 , wherein the at least one processor is further configured to execute the instructions to:

scan at most 8 pixels along the circumferential direction centered on the first boundary pixel identified in the secondary image; and

scan at most 7 pixels along the circumferential direction centered on the second boundary pixel identified in the secondary image.

10 . The electronic device of claim 1 , wherein the complete contour of the object is obtained when a last boundary pixel is identified as satisfying the boundary criteria during the scanning the secondary image.

11 . The electronic device of claim 1 , wherein the at least one processor is further configured to execute the instructions to:

split the secondary image to a plurality of image segments;

obtain, in parallel, a respective contour of the object in each of the plurality of image segments; and

obtain the complete contour of the object in the secondary image based on the respective contour of the object in each of the plurality of image segments.

12 . The electronic device of claim 11 , wherein an edge boundary pixel is excluded from the complete contour of the object, and wherein the edge boundary pixel is located at an intersection edge of each of the plurality of image segments.

13 . The electronic device of claim 11 , wherein the plurality of image segments comprise a first quadrant image segment, a second quadrant image segment, a third quadrant image segment, and a fourth quadrant image segment,

wherein a first scan direction from a first start pixel in the first quadrant image segment and a fourth scan direction from a fourth start pixel in the fourth quadrant image segment are identical,

wherein a second scan direction from a second start pixel in the second quadrant image segment and a third scan direction from a third start pixel in the third quadrant image segment are identical, and

wherein the first scan direction and the second scan direction are opposite.

14 . A method comprising:

processing an image to output a secondary image;

splitting the secondary image into a plurality of image segments;

scanning the secondary image in a scan direction from a start pixel in each of the plurality of image segments to identify a first boundary pixel found as satisfying a boundary criteria during the scanning of the secondary image;

identifying a second boundary pixel satisfying the boundary criteria by rotating the scan direction and scanning pixels in the secondary image along a circumferential direction centered on the first boundary pixel, wherein the scanning of the pixels starts from a pixel that is adjacent to the first boundary pixel, located in the rotated scan direction and adjacent to a direction opposite to the scan direction;

identifying one or more next boundary pixels until a respective contour of an object is obtained in each of the plurality of image segments; and

obtaining a complete contour of the object in the secondary image based on the respective contours obtained in the plurality of image segments,

wherein scan directions used for at least two different image segments are opposite to each other.

15 . A computer program product comprising a non-transitory computer-readable recording medium having recorded thereon a program executable by a computer for performing a method comprising:

processing an image to output a secondary image;

splitting the secondary image into a plurality of image segments;

scanning the secondary image in a scan direction from a start pixel in each of the plurality of image segments to identify a first boundary pixel found as satisfying a boundary criteria during the scanning of the secondary image;

identifying a second boundary pixel satisfying the boundary criteria by rotating the scan direction and scanning pixels in the secondary image along a circumferential direction centered on the first boundary pixel, wherein the scanning of the pixels starts from a pixel that is adjacent to the first boundary pixel, located in the rotated scan direction and adjacent to a direction opposite to the scan direction;

identifying one or more next boundary pixels until a respective contour of an object is obtained in each of the plurality of image segments; and

obtaining a complete contour of the object in the secondary image based on the respective contours obtained in the plurality of image segments,

wherein scan directions used for at least two different image segments are opposite to each other.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 26, 2023
From: A K, MAHESH BABU
To: SAMSUNG ELECTRONICS CO., LTD.
Reel/Frame 063776/0458 →
Priority Claims (1)
IN 202011053808 · Dec 10, 2020 · national
Continuity (2)
Continuation PCTKR2021018797 · Dec 10, 2021
Related Publication 20230306609A1 · Sep 28, 2023
References Cited (55)
US 5119439A · Osawa · 1992 [cited by examiner]
US 5621819A · Hozumi · 1997 [cited by examiner]
US 5778105A · Shively · 1998 [cited by examiner]
US 5825922A · Pearson · 1998 [cited by examiner]
US 6268933B1 · Kim · 2001 [cited by examiner]
US 6356657B1 · Takaoka · 2002 [cited by examiner]
US 6674904B1 · McQueen · 2004 [cited by examiner]
US 7313254B2 · Lee et al. · 2007 [cited by applicant]
US 7805006B2 · Katsuyama et al. · 2010 [cited by applicant]
US 7916912B2 · Abramov · 2011 [cited by examiner]
US 7973986B2 · Ishiguro · 2011 [cited by examiner]
US 8675059B2 · Johnson · 2014 [cited by examiner]
US 8786903B2 · Suzuki · 2014 [cited by applicant]
US 9164588B1 · Johnson et al. · 2015 [cited by applicant]
US 10395364B2 · Hamada · 2019 [cited by examiner]
US 10510148B2 · Qiu · 2019 [cited by examiner]
US 10997743B2 · Ikeda · 2021 [cited by examiner]
US 11216925B2 · Zhang et al. · 2022 [cited by applicant]
US 11336906B2 · Xu · 2022 [cited by applicant]
US 12382064B2 · Kirchhoffer · 2025 [cited by examiner]
US 20030174890A1 · Yamauchi · 2003 [cited by applicant]
US 20070098264A1 · Van Lier et al. · 2007 [cited by applicant]
US 20120219227A1 · Osako · 2012 [cited by examiner]
US 20120275701A1 · Park · 2012 [cited by examiner]
US 20130322771A1 · Poyil et al. · 2013 [cited by applicant]
US 20150046886A1 · Goel et al. · 2015 [cited by applicant]
US 20180276837A1 · Amano · 2018 [cited by examiner]
US 20180322656A1 · Dworakowski et al. · 2018 [cited by applicant]
US 20190102885A1 · Yamaguchi · 2019 [cited by applicant]
US 20190287258A1 · Mano et al. · 2019 [cited by applicant]
US 20210035318A1 · Nakagawa · 2021 [cited by examiner]
US 20210334998A1 · Chu · 2021 [cited by examiner]
US 20220215557A1 · Xu et al. · 2022 [cited by applicant]
CN 1797030A · 2006 [cited by applicant]
CN 107194938A · 2017 [cited by applicant]
CN 110428434A · 2019 [cited by examiner]
KR 1020040035981A · 2004 [cited by applicant]
KR 100568531B1 · 2006 [cited by applicant]
KR 1020060100376A · 2006 [cited by applicant]
KR 101167976B1 · 2012 [cited by examiner]
KR 101528604B1 · 2015 [cited by applicant]
KR 1020150103902A · 2015 [cited by applicant]
KR 101911912B1 · 2018 [cited by applicant]
WO 2017129573A1 · 2017 [cited by applicant]
WO 2020228187A1 · 2020 [cited by applicant]
WO WO2021174506A1 · 2021 [cited by examiner]
“Boundary tracing”, Wikipedia, Sep. 2022, 3 pages total. [cited by applicant]
Communication dated Jul. 6, 2022 issued by the Indian Patent Office in counterpart Indian Application No. 202011053808. [cited by applicant]
S.P.Maniraj et al., “Object Boundary Detection using Neural Network in Deep Learning”, International Journal of Engineering and Advanced Technology (IJEAT), vol. 9, Issue 1, Oct. 2019, 5 pages total. [cited by applicant]
Piotr Dollár et al., “Supervised Learning of Edges and Object Boundaries”, Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06), Jun. 2006, 8 pages total. [cited by applicant]
Communication dated Mar. 21, 2022 issued by the International Searching Authority in counterpart Application No. PCT/KR2021/018797 (PCT/ISA/220, PCT/ISA/210, and PCT/ISA/237). [cited by applicant]
Jonghoon Seo et al., “Fast Contour-Tracing Algorithm Based on a Pixel-Following Method for Image Sensors”, Sensors, vol. 16, Issue. 3, 353, Mar. 9, 2016, 56 pages total. [cited by applicant]
Seokmok Park et al., “A Novel Comer Detector using a Non-cornerness Measure”, IEIE Transactions on Smart Processing and Computing, vol. 6, No. 4, Aug. 30, 2017, 10 pages total. [cited by applicant]
Vijay Sukhadeve, “uWave: Accelerometer-based Personalized Gesture Recognition and Its Applications”, Dec. 2009, 23 pages total. [cited by applicant]
“Image Recognition Market by Technology (Digital Image Processing, Facial Recognition, Pattern Recognition), Component (Hardware, Software, and Services), Deployment Mode (On-premises & Cloud), Application, Vertical, an… [cited by applicant]