Image Control System Selecting Interest Images for Retrieval
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Solution Overview
Problem
Existing image control systems face reduced retrieval rates and inefficient storage management as the volume of input images from CCTVs increases, as they store and retrieve metadata for all images without prioritizing images of interest based on complexity and quality.
Innovation Solution
An image control system that selects images of interest by calculating complexity and image quality scores, using both bottom-up and top-down approaches, and stores only these images in a retrieval database, reducing the search space and optimizing storage usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all images are stored in the retrieval database, then complete image coverage is achieved, but storage space consumption increases and retrieval efficiency decreases
Solution Approach 1:
The patent extracts only the essential and valuable images from the complete image set for storage in the retrieval database. By using image quality assessment and object detection algorithms, the system identifies and extracts images containing objects of interest with sufficient quality, storing only these extracted images rather than all images, thereby reducing storage space while maintaining retrieval effectiveness
Solution Approach 2:
The patent applies local quality assessment to different regions and characteristics of images. Instead of uniformly evaluating all images, the system assesses local regions containing potential objects of interest, evaluating their quality and significance locally. This allows selective storage of images with high-quality regions containing valuable objects, optimizing the balance between storage space and retrieval completeness
2Reliability
If all images are stored in the retrieval database, then complete image coverage is achieved, but retrieval time increases
Solution Approach 1:
The patent extracts only the essential and valuable images from the complete image set for storage in the retrieval database. By using image quality assessment and object detection algorithms, the system identifies and extracts images containing objects of interest with sufficient quality, storing only these extracted images rather than all images, thereby reducing storage space while maintaining retrieval effectiveness
Solution Approach 2:
The patent performs preliminary assessment and selection of images before they are stored in the retrieval database. The system pre-evaluates images using quality metrics and object detection, pre-identifying which images contain objects of interest. This preliminary action filters the image set beforehand, so that when retrieval is needed, the search is already limited to pre-selected relevant images, significantly reducing retrieval time
3Productivity
If image selection based on complexity and quality is implemented, then storage efficiency and retrieval speed improve, but system complexity increases
Solution Approach 1:
The patent performs preliminary assessment and selection of images before they are stored in the retrieval database. The system pre-evaluates images using quality metrics and object detection, pre-identifying which images contain objects of interest. This preliminary action filters the image set beforehand, so that when retrieval is needed, the search is already limited to pre-selected relevant images, significantly reducing retrieval time
Solution Approach 2:
The patent introduces specific parameters for image quality assessment and complexity evaluation to automate the selection process. By defining quantitative parameters such as image quality scores, object detection confidence levels, and complexity metrics, the system transforms subjective selection criteria into objective, computable parameters. This parameter-based approach enables automated decision-making, improving retrieval efficiency while managing system complexity through standardized evaluation metrics
Data Source
AI summary
Exemplary embodiments relate to a method for selecting an image of interest to construct a retrieval database including receiving an image captured by an imaging device, detecting an object of interest in the received image, selecting an image of interest based on at least one of complexity of the image in which the object of interest is detected and image quality of the object of interest, and storing information related to the image of interest in the retrieval database, and an image control system performing the same.