IP Library Granted Patent US 12,505,556
Granted Patent B2
US 12,505,556 · App. 18/359,086 · Granted Dec 23, 2025

Corner point detection method and apparatus

Inventors: Lei Zhang (Ningde, CN); Guannan Jiang (Ningde, CN); Fei Chen (Ningde, CN)
Assignee: CONTEMPORARY AMPEREX TECHNOLOGY (HONG KONG) LIMITED
G06T7/13G06T7/0004G06T7/136G06V10/44G06T2207/20164G06T2207/30164
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 12,505,556
App. No.
18/359,086
Granted
Dec 23, 2025
Kind
B2
Abstract

A corner point detection method and apparatus, which may improve the efficiency of corner point detection is disclosed. The corner point detection method includes: obtaining a plurality of corner points of a target object in an image to be detected, where the plurality of corner points are corner points on a contour of a first object in the image to be detected, and the contour of the first object includes a contour of the target object; obtaining a region proportion corresponding to each of the plurality of corner points, where the region proportion is a proportion of a region of the first object in a predetermined region centered on the corner point; and determining a target corner point of the target object from the plurality of corner points based on the region proportion.

Claims (25)

1 . A processor implemented corner point detection method, comprising:

obtaining a plurality of corner points of a target object in an image to be processed, wherein the plurality of corner points are corner points on a contour of a first object in the image to be processed, and the contour of the first object comprises a contour of the target object;

wherein the obtaining a plurality of corner points of a target object in an image to be processed comprises: obtaining the plurality of corner points in a region of interest in the image to be processed;

obtaining a region proportion for each of the plurality of corner points, wherein the region proportion is a proportion of a region of the first object in a predetermined region of the image to be processed, centered on the corner point; and

determining a target corner point of the target object from the plurality of corner points based on the region proportion;

wherein the determining a target corner point of the target obiect from the plurality of corner points based on the region proportion comprises:

obtaining at least one candidate corner point whose region proportion is greater than a predetermined value from the plurality of corner points; and

obtaining the target corner point from the at least one candidate corner point;

wherein the obtaining the target corner point from the at least one candidate corner point comprises:

determining there are a plurality of candidate corner points, and subsequently determining the target corner point based on a location relationship between each of the plurality of candidate corner points and a center point of the target object.

2 . The method according to claim 1 , wherein the determining the target corner point based on a location relationship between each of the plurality of candidate corner points and a center point of the target object comprises: determining, as the target corner point, a candidate corner point of the plurality of candidate corner points that is at a maximum vertical distance from a location of the center point of the target object.

3 . The method according to claim 1 , further comprising:

determining at least one region of interest in the image to be processed.

4 . The method according to claim 1 , wherein the obtaining a plurality of corner points of a target object in an image to be processed comprises: obtaining the contour of the first object in the region of interest to obtain a target contour, wherein the target contour comprises the contour of the target object;

and obtaining corner points on the target contour to obtain the plurality of corner points.

5 . The method according to claim 4 , wherein the obtaining corner points on the target contour to obtain the plurality of corner points comprises:

obtaining a polygon corresponding to the target contour by using a polygon approximation method; and

obtaining vertices of the polygon to obtain the plurality of corner points.

6 . The method according to claim 4 , wherein before obtaining the contour of the first object in the region of interest, the method further comprises: performing binarization on the image to be processed, to obtain a binary image of the image to be processed; and obtaining the contour of the first object based on an edge of the binary image.

7 . The method according to claim 1 , wherein the predetermined region is in the shape of a circle.

8 . The method according to claim 7 , wherein a radius of the circle is ten pixels.

9 . The method according to claim 1 , wherein the predetermined value is 0.6.

10 . The method according to claim 1 , wherein the target object is a tab.

11 . A corner point detection apparatus, comprising a processor and a memory, wherein the memory is configured to store a program, and the processor is configured to invoke the program from the memory and execute the program to perform a corner point detection method according to claim 1 .

12 . A non-transitory computer-readable storage medium, comprising a computer program that, when executed on a computer, causes the computer to perform a corner point detection method according to claim 1 .

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 6, 2024
From: CONTEMPORARY AMPEREX TECHNOLOGY CO., LIMITED
To: CONTEMPORARY AMPEREX TECHNOLOGY (HONG KONG) LIMITED
Reel/Frame 068338/0402 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 26, 2023
From: ZHANG, LEI; JIANG, GUANNAN; CHEN, FEI
To: CONTEMPORARY AMPEREX TECHNOLOGY CO., LIMITED
Reel/Frame 064386/0070 →
Priority Claims (1)
CN 202210841619.X · Jul 18, 2022 · national
Continuity (2)
Continuation PCTCN2023081107 · Mar 13, 2023
Related Publication 20240020846A1 · Jan 18, 2024
References Cited (33)
US 20150104106A1 · Elinas et al. · 2015 [cited by applicant]
US 20150178593A1 · Shen et al. · 2015 [cited by applicant]
US 20200134682A1 · Sethi · 2020 [cited by examiner]
US 20230184690A1 · Kim · 2023 [cited by examiner]
CN 103927750A · 2014 [cited by applicant]
CN 107341802A · 2017 [cited by examiner]
CN 107816951A · 2018 [cited by applicant]
CN 107833217A · 2018 [cited by applicant]
CN 108229433A · 2018 [cited by applicant]
CN 108875723A · 2018 [cited by applicant]
CN 108898147A · 2018 [cited by applicant]
CN 109409366A · 2019 [cited by applicant]
CN 109509200A · 2019 [cited by applicant]
CN 110569857A · 2019 [cited by applicant]
CN 110992326A · 2020 [cited by applicant]
CN 111047614A · 2020 [cited by applicant]
CN 111681284A · 2020 [cited by applicant]
CN 111832659A · 2020 [cited by applicant]
CN 111986219A · 2020 [cited by applicant]
CN 112528847A · 2021 [cited by applicant]
CN 112669365A · 2021 [cited by applicant]
CN 113409334A · 2021 [cited by applicant]
CN 113888456A · 2022 [cited by applicant]
CN 113920324A · 2022 [cited by applicant]
CN 114445499A · 2022 [cited by applicant]
WO 2022148192A1 · 2022 [cited by applicant]
ISR for International Application PCT/CN2023/081107 dated May 10, 2023. [cited by applicant]
Written Opinion for International Application PCT/CN2023/081107 dated May 10, 2023. [cited by applicant]
Chinese Office Action for counterpart application CN-202210841619.X dated Jun. 14, 2023. [cited by applicant]
Li Houjie et al.: “Separation Algorithm of Traffic Signs Based on Curvature Scale Space Corner Detection” Acta Optica Sinica vol. 35, No. 1, Jan. 2015(Jan. 1, 2015). [cited by applicant]
China Second Office Action for Application No. 202210841619.X, dated Apr. 25, 2024, 9 pages. [cited by applicant]
Extended European Search Report for Application No. PCT/CN2023081107, dated Jul. 2, 2024, 6 pages. [cited by applicant]
G. Guo et al., “Automatic Video Text Localization and Recognition,” Fourth International Conference on Image and Graphics (ICIG 2007), Chengdu, China, Aug. 1, 2007, pp. 484-489. [cited by applicant]