IP Library › Granted Patent US 12,567,153
Granted Patent B2
US 12,567,153 · App. 18/299,707 · Granted Mar 3, 2026

Electronic device and method for selecting region of interest in image

Inventors: Kuo-Huang Hsu (Taoyuan City, TW); An-Kai Jeng (Hsinchu City, TW)
Assignee: Industrial Technology Research Institute
G06T7/11G06T7/174H04N7/0127G06T2207/30241G06T2207/30261
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Quick Facts
Patent No.
US 12,567,153
App. No.
18/299,707
Granted
Mar 3, 2026
Kind
B2
Abstract

Disclosed are an electronic device and a method for selecting a region of interest in an image. The method includes the following steps: receiving an image; using the image to obtain a plurality of regions of interest, wherein each of the plurality of regions of interest corresponds to an object danger level value; and using the object danger level value to select a first region of interest from the plurality of regions of interest.

Claims (28)

1 . An electronic device for selecting regions of interest (ROIs) in an image, comprising:

a transceiver; and

a processor coupled to the transceiver and configured to:

receive images through the transceiver;

obtain a plurality of ROIs by using the images, wherein each of the plurality of ROIs corresponds to an object danger level value;

use the object danger level value to select a first ROI from the plurality of ROIs; and

use a maximum throughput and a number of frames per second to determine a maximum data size value per frame.

2 . The electronic device of claim 1 , wherein the plurality of ROIs comprises the first ROI and a plurality of other ROIs, and the object danger level value corresponding to the first ROI is greater than the object danger level value corresponding to each of the plurality of other ROIs.

3 . The electronic device of claim 1 , wherein the first ROI corresponds to a transmission bandwidth value of the first ROI, wherein a sum of a minimum resolution data size value of a single image without ROI in the image and the transmission bandwidth value of the first ROI is less than or equal to the maximum data size value per frame.

4 . The electronic device of claim 1 , wherein the first ROI corresponds to a transmission bandwidth value of the first ROI, wherein a sum of a minimum resolution data size value of a single image without ROI in the image and the transmission bandwidth value of the first ROI is less than or equal to the maximum data size value per frame.

5 . The electronic device of claim 1 , wherein the first ROI corresponds to a transmission bandwidth value of the first ROI, and the plurality of ROIs comprise the first ROI and a plurality of other ROIs, wherein the processor is further configured to:

select a second ROI from the plurality of other ROIs, wherein the second ROI is different from the first ROI, wherein the second ROI corresponds to a transmission bandwidth value of the second ROI, and a sum of a minimum resolution data size value of a single image without ROI in the image, the transmission bandwidth value of the first ROI, and the transmission bandwidth value of the second ROI is less than or equal to the maximum data size value per frame.

6 . The electronic device of claim 1 , wherein the first ROI corresponds to a transmission bandwidth value of the first ROI, wherein the processor is further configured to:

when a sum of the transmission bandwidth value of the first ROI and a minimum resolution data size value of a single image without ROI in the image is greater than the maximum data size value per frame, adjust the number of frames per second based on the maximum throughput, the transmission bandwidth value of the first ROI, and the minimum resolution data size value of the single image without ROI.

7 . The electronic device of claim 1 , wherein the object danger level value is Time to Collision (TTC).

8 . A method for selecting ROIs in an image, comprising:

receiving images;

obtaining a plurality of ROIs by using the images, wherein each of the plurality of ROIs corresponds to an object danger level value;

selecting a first ROI from the plurality of ROIs by using the object danger level value; and

determining a maximum data size value per frame by using a maximum throughput and a number of frames per second.

9 . The method of claim 8 , wherein the plurality of ROIs comprise the first ROI and a plurality of other ROIs, and the object danger level value corresponding to the first ROI is greater than the object danger level value corresponding to each of the plurality of other ROIs.

10 . The method of claim 8 , wherein the first ROI corresponds to a transmission bandwidth value of the first ROI, wherein a sum of a minimum resolution data size value of a single image without ROI in the image and the transmission bandwidth value of the first ROI is less than or equal to the maximum data size value per frame.

11 . The method of claim 8 , wherein the first ROI corresponds to a transmission bandwidth value of the first ROI, wherein a sum of a minimum resolution data size value of a single image without ROI in the image and the transmission bandwidth value of the first ROI is less than or equal to the maximum data size value per frame.

12 . The method of claim 8 , wherein the first ROI corresponds to a transmission bandwidth value of the first ROI, and the plurality of ROIs comprise the first ROI and a plurality of other ROIs, wherein the method further comprises:

selecting a second ROI from the plurality of other ROIs, wherein the second ROI is different from the first ROI, wherein the second ROI corresponds to a transmission bandwidth value of the second ROI, and a sum of a minimum resolution data size value of a single image without ROI in the image, the transmission bandwidth value of the first ROI, and the transmission bandwidth value of the second ROI is less than or equal to the maximum data size value per frame.

13 . The method of claim 8 , wherein the first ROI corresponds to a transmission bandwidth value of the first ROI, wherein the method further comprises:

when a sum of the transmission bandwidth value of the first ROI and a minimum resolution data size value of a single image without ROI in the image is greater than the maximum data size value per frame, adjusting the number of frames per second based on the maximum throughput, the transmission bandwidth value of the first ROI, and the minimum resolution data size value of the single image without ROI.

14 . The method of claim 8 , wherein the object danger level value is TTC.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 17, 2023
From: HSU, KUO-HUANG; JENG, AN-KAI
To: INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE
Reel/Frame 063336/0275 →
Priority Claims (1)
TW 112106992 · Feb 24, 2023 · national
Continuity (1)
Related Publication 20240289961A1 · Aug 29, 2024
References Cited (56)
US 7848237B2 · Todd et al. · 2010 [cited by applicant]
US 8296813B2 · Berkey · 2012 [cited by examiner]
US 10250923B2 · Gilson · 2019 [cited by examiner]
US 10780881B2 · You · 2020 [cited by applicant]
US 10805696B1 · Suiter · 2020 [cited by examiner]
US 11048927B2 · Russell · 2021 [cited by examiner]
US 11284021B1 · Cardei · 2022 [cited by examiner]
US 11301692B2 · Oami · 2022 [cited by examiner]
US 11556126B2 · Hammond · 2023 [cited by examiner]
US 12131637B2 · Takada · 2024 [cited by examiner]
US 20140300466A1 · Park · 2014 [cited by examiner]
US 20150328985A1 · Kim · 2015 [cited by examiner]
US 20150332103A1 · Yokota · 2015 [cited by examiner]
US 20160275642A1 · Abeykoon · 2016 [cited by examiner]
US 20180308202A1 · Appu · 2018 [cited by examiner]
US 20190035154A1 · Liu · 2019 [cited by examiner]
US 20190087198A1 · Frascati · 2019 [cited by examiner]
US 20200288066A1 · Candelore · 2020 [cited by examiner]
US 20200317190A1 · Tong · 2020 [cited by examiner]
US 20200321374A1 · Ion · 2020 [cited by examiner]
US 20210027076A1 · Hayashi · 2021 [cited by examiner]
US 20210081676A1 · Kim · 2021 [cited by examiner]
US 20210182573A1 · Sabeti · 2021 [cited by examiner]
US 20210329413A1 · Hsu · 2021 [cited by examiner]
US 20210407223A1 · Anabuki · 2021 [cited by examiner]
US 20220169245A1 · Hieida · 2022 [cited by examiner]
US 20220215201A1 · Dwivedi · 2022 [cited by examiner]
US 20220292827A1 · Chen · 2022 [cited by examiner]
US 20250191383A1 · Hahn · 2025 [cited by examiner]
US 20250292684A1 · Muthiah · 2025 [cited by examiner]
CN 103987577 · 2017 [cited by applicant]
CN 114119955 · 2022 [cited by applicant]
DE 102015216352 · 2017 [cited by applicant]
EP 1862940 · 2007 [cited by applicant]
EP 2461272 · 2012 [cited by applicant]
EP 4421751A1 · 2024 [cited by examiner]
TW I520612 · 2016 [cited by applicant]
TW I560469 · 2016 [cited by applicant]
TW I563825 · 2016 [cited by applicant]
TW I636683 · 2018 [cited by applicant]
WO 9949412 · 1999 [cited by applicant]
WO WO2020172842A1 · 2020 [cited by examiner]
WO WO2023189084A1 · 2023 [cited by examiner]
WO WO2024090328A1 · 2024 [cited by examiner]
J. Meessen et al., “WCAM: Smart Encoding for Wireless Surveillance”, SPIE, Image and Video Communications and Processing 2005, Mar. 14, 2005, pp. 14-25, vol. 5685. [cited by applicant]
Hui Li et al., “Dynamic region-based wavelet compression for telemedicine application”, SPIE, Medical Imaging 1997: Image Display, May 7, 1997, pp. 851-859, vol. 3031. [cited by applicant]
“Search Report of Europe Counterpart Application”, issued on Sep. 15, 2023, p. 1-p. 12. [cited by applicant]
Guntur Ravindra et al., “In-network Optimal Rate Reduction for Packetized MPEG Video”, Q2SWinet '08, Oct. 27-28, 2008, pp. 55-61. [cited by applicant]
Ravindra G, N Balakrishnan et al., “Active Router Approach for Selective Packet Discard of Streamed MPEG video under Low Bandwidth Conditions”, 2000 IEEE International Conference on Multimedia and Expo, Jul. 30, 2000-Au… [cited by applicant]
Anastasios Doulamis et al., “Optimal Multi-Content Video Decomposition for Efficient Video Transmission over Low-Bandwidth Networks”, 2002 International Conference on Image Processing, Sep. 22-25, 2002, pp. II-201-II-20… [cited by applicant]
Zhenli Zhou et al., “A User-driven Interactive 3D Video Streaming Transmission System with Low Network Bandwidth Requirements”, 2012 International Conference on Advanced Communication Technology, Feb. 19-22, 2012, pp. 1… [cited by applicant]
Anastasios Doulamis et al., “Content-based Video Adaptation in Low/Variable Bandwidth Communication Networks Using Adaptable Neural Network Structures”, 2006 International Joint Conference on Neural Networks, Jul. 16-21… [cited by applicant]
Hexiang Qiao et al., “Crowd Intelligence Empowered Video Transmission in Ultra-low-bandwidth Constrained Circumstances”, 2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Compu… [cited by applicant]
Umang Goenka et al., “Threat Detection In Self Driving Vehicles Using Computer Vision”, Machine Learning, Image Processing, Network Security and Data Sciences. Lecture Notes in Electrical Engineering, Sep. 6, 2022, pp. … [cited by applicant]
Young-Bin Shim et al., “A Study on Surveillance System of Object's Abnormal Behavior by Blob Composition Analysis”, International Journal of Security and Its Applications, Mar. 31, 2014, pp. 333-340, vol. 8, No. 2. [cited by applicant]
“Office Action of Europe Counterpart Application”, issued on Sep. 24, 2025, p. 1-p. 6. [cited by applicant]