Image Analysis System Using Similar Image Retrieval
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Solution Overview
Problem
Existing image analysis systems require pre-setting of imaging conditions before capturing images, making them inadequate for processing large volumes of images from various sources like UAVs, wearable devices, and security cameras, where environmental conditions can vary significantly.
Innovation Solution
A system that stores analyzed images with associated camera settings and object data, extracts similar images from a database, and applies the corresponding imaging environment data set for enhanced analysis of newly acquired images, improving detection and identification accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pre-setting of imaging conditions is required before capturing images, then image analysis accuracy can be improved under controlled conditions, but the system becomes inadequate for processing large volumes of images from various sources with varying environmental conditions
Solution Approach 1:
The system performs preliminary actions by storing imaging environment data sets from past images along with their analysis results. When a new image is acquired, the system retrieves and applies the imaging environment data set from a similar past image, thereby preparing the analysis parameters in advance without requiring pre-setting for each new image. This resolves the contradiction by enabling accurate analysis through pre-collected data while maintaining adaptability to various imaging conditions.
Solution Approach 2:
The system creates a copy of the imaging environment data set from a similar past image and applies it to the current image analysis. Instead of requiring original pre-setting for each new image source, the system copies relevant environmental parameters (such as lighting conditions, camera settings, object characteristics) from historically similar images. This allows the system to adapt to various imaging sources while maintaining analysis accuracy through replicated environmental contexts.
2Measurement precision
If imaging environment data is stored and applied from similar past images, then analysis accuracy for varying conditions is improved, but system complexity increases due to database management and similarity matching
Solution Approach 1:
The system performs self-service by automatically managing the imaging environment data set database and executing similarity matching without requiring complex external control systems. The acquisition unit automatically acquires images, the similar image extraction unit autonomously identifies matching past images based on environmental parameters, and the image analysis unit self-applies the appropriate data sets. This self-service mechanism reduces system complexity while maintaining high detection and identification accuracy through automated data retrieval and application.
3Reliability
If pre-setting is required before image capture, then controlled environment analysis is reliable, but real-time processing of already-taken images cannot be performed
Solution Approach 1:
The system performs preliminary action by pre-collecting and storing imaging environment data sets from various conditions before they are needed for analysis. When images are already taken, the system can immediately retrieve the appropriate pre-stored data set through similarity matching, enabling real-time post-processing without the time delays associated with acquiring new environmental data. This maintains reliability by using pre-validated environmental parameters while eliminating processing delays.
Data Source
AI summary
The system for image analysis that analyzes an image taken by a camera improves the accuracy of detection and identification an object in image analysis. The system stores a plurality of analyzed past images and their imaging environment data sets that include setting data of a camera that took the past image and data on an object; includes an acquisition module 211 that acquires an image and a similar image extraction module 212 that extracts a past image similar to the image; and applies the imaging environment data set of the extract past image to the acquired image and analyzes the acquired image.