Image Analysis System Using Environment Data Matching
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Solution Overview
Problem
Existing image analysis systems require pre-setting of imaging parameters, making them inefficient for processing images taken by cameras on vehicles or security cameras, as they are time-consuming and not adaptable to varying environments.
Innovation Solution
A system that detects the imaging environment and matches it with stored data sets to apply appropriate parameters for improved detection and identification, including a memory unit for storing imaging environment data, a detection unit, a check unit, and an extraction unit to select the best parameters for image analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pre-setting of imaging parameters is performed before image capture, then detection and identification accuracy is improved, but the system becomes time-consuming and cannot process images already taken
Solution Approach 1:
The system performs preliminary actions by capturing imaging environment data (illumination, angle, distance) at the time of image capture and storing it alongside the image. This preliminary data collection enables later retrieval and application of appropriate analysis parameters without requiring pre-setting before each image processing task, thus improving both accuracy and efficiency.
Solution Approach 2:
The patent introduces imaging environment data as an intermediary element that bridges the image and the analysis parameters. This intermediary contains information about illumination conditions, camera angle, and distance, which are used to automatically select appropriate detection and identification parameters, eliminating the need for time-consuming manual pre-setting while maintaining high accuracy.
2Measurement precision
If manual parameter adjustment is performed to improve detection and identification, then accuracy is improved, but the process becomes time-consuming and troublesome
Solution Approach 1:
The system implements self-service by automatically selecting detection and identification parameters based on the stored imaging environment data. The image analysis unit retrieves the imaging environment data (illumination, angle, distance) and automatically determines the appropriate analysis parameters without requiring manual intervention, thus improving both accuracy and operational simplicity.
Solution Approach 2:
The system uses feedback from the imaging environment data to automatically adjust analysis parameters. The imaging environment data captured at the time of image taking provides feedback information about the shooting conditions, which the system uses to select the most appropriate detection and identification parameters, eliminating manual adjustment while maintaining high accuracy.
3Productivity
If fixed analysis parameters are used for all images, then processing speed is improved, but accuracy deteriorates in varying imaging environments
Solution Approach 1:
The system implements dynamic parameter selection by linking analysis parameters to imaging environment data. Instead of using fixed parameters for all images, the system dynamically selects appropriate parameters based on the specific imaging conditions (illumination, angle, distance) captured at the time of each image, thus maintaining both high processing speed and high accuracy across varying environments.
Solution Approach 2:
The patent applies parameter changes by automatically adjusting detection and identification parameters based on imaging environment variations. The system changes analysis parameters according to the stored imaging conditions (different illumination levels, camera angles, and distances), ensuring optimal accuracy for each specific imaging scenario while maintaining efficient automated processing.
Data Source
AI summary
The system for image analysis that analyzes an image taken by a camera improves the accuracy of detection and identification in image analysis. The system memorizes a plurality of imaging environment data sets that include setting data of a camera and data on an object; includes a detection module 211 that detects an imaging environment from the camera, a check module 212 that checks the imaging environment, and an extraction module 213 that extracts an imaging environment data set similar to the detected imaging environment; and applies the extracted imaging environment data set and analyzes an image.