Real-Time Image Correcting Device for Remote Surveillance
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Solution Overview
Problem
In remote surveillant and medical imaging systems, maintenance staffs face challenges in immediately repairing devices due to unstable image inputs, leading to lost recordings and misjudgments, and existing reboot methods are time-consuming, disrupting critical operations.
Innovation Solution
A correcting device and method that automatically detect image status, compute motion vectors, and perform real-time corrections or resets to ensure stable image output, using an image detecting module, comparing module, controlling module, and correcting module to analyze and compensate image features and vectors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system reboots through remote instruction to solve abnormal input images, then the abnormal issue may be solved, but it takes minutes for the entire system to reboot and restore to prepared status, causing time loss in critical operations
Solution Approach 1:
The patent segments the image processing system into multiple independent components: image capturing device, image processing device, and correcting device. This segmentation allows the correcting device to operate independently and correct images without requiring a full system reboot, thus resolving the contradiction between maintaining image quality and minimizing time loss.
Solution Approach 2:
The correcting device acts as an intermediary component between the image processing device and the output display. It receives images from the image processing device, corrects abnormal images through image correction algorithms, and outputs corrected images. This intermediary approach enables image correction without interrupting the overall system operation, eliminating the need for time-consuming reboots while maintaining image reliability.
2Reliability
If manual reboot is performed to restore system status, then the system may return to normal operation, but maintenance staffs cannot immediately repair devices in remote or inaccessible areas, leading to lost recordings and misjudgments
Solution Approach 1:
The correcting device implements self-service functionality by automatically detecting abnormal images and correcting them without requiring manual intervention from maintenance staff. The device monitors image quality in real-time, identifies abnormalities through image comparison algorithms, and applies corrections autonomously. This self-service capability ensures image stability in remote locations where maintenance staff cannot immediately intervene, preventing lost recordings and misjudgments.
Solution Approach 2:
The system incorporates feedback mechanisms where the correcting device continuously monitors output images and compares them against expected quality standards. When abnormalities are detected, the system automatically adjusts correction parameters and applies corrections. This closed-loop feedback system maintains image stability without requiring physical access to the device, solving the accessibility problem in remote deployments.
3Measurement precision
If the image processing software stops capturing and recording when images appear interrupted, then false interruptions may be avoided, but important images will be lost of recording when images are temporarily unstable
Solution Approach 1:
The correcting device performs preliminary correction actions on images before they are output or stored. Instead of waiting for images to be fully processed and then detecting interruptions, the device proactively identifies and corrects abnormalities in real-time during the image processing pipeline. This preliminary action ensures that temporarily unstable images are corrected rather than discarded, preventing loss of important recorded images while maintaining detection precision.
Solution Approach 2:
The system implements a buffer mechanism where the correcting device maintains a queue of images and uses image comparison algorithms to identify temporary instabilities versus actual interruptions. By cushioning the image stream through this correction buffer, the system can distinguish between transient quality issues that should be corrected and genuine interruptions that warrant stopping recording, thus preventing loss of important images while maintaining accurate detection.
Data Source
AI summary
A correcting method of a real-time image is disclosed and includes: continuously receiving real-time images from an image inputting device; analyzing an image feature in each real-time image; computing a motion vector of each real-time image based on a feature difference between any two time-adjacent real-time images; computing a moving trajectory predicted value of a latest real-time image based on accumulated motion vectors; computing a compensation value of the latest real-time image when determining that a difference between the moving trajectory predicted value and the motion vector of the latest real-time image is within a correction allowable range, and correcting the latest real-time image by the compensation value; and, resetting the image inputting device and outputting a default image when determining that the difference between the moving trajectory and the motion vector of the latest real-time image exceeds the correction allowable range.