Imaging Support Device Frequency-Based Subject Prioritization
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Solution Overview
Problem
Current imaging technologies lack the ability to effectively support imaging based on the frequency of subject features classified into categories, leading to inefficient image capture and processing.
Innovation Solution
An imaging support device and method that acquires frequency information of subject features from captured images, classifying them into categories and performing support processing to enhance imaging operations, including display and focus adjustments based on the frequency data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If imaging is performed without frequency-based subject classification, then imaging operations are simple, but imaging efficiency and target accuracy deteriorate
Solution Approach 1:
The system performs preliminary classification of subjects into categories and calculates capture frequencies before actual imaging occurs. This advance preparation enables the imaging apparatus to prioritize targets based on predefined criteria, improving imaging efficiency without adding complexity during the actual capture process
Solution Approach 2:
An imaging support device acts as an intermediary between the imaging apparatus and the user. This mediator analyzes subject features, categorizes them, determines capture frequencies, and generates guidance information, thereby improving imaging efficiency while isolating the complexity from the main imaging system
2Productivity
If all subjects are captured with equal priority, then imaging coverage is comprehensive, but imaging efficiency for specific targets deteriorates
Solution Approach 1:
The system applies different quality levels of processing to different subjects based on their category and capture frequency. High-priority targets receive enhanced processing and guidance, while lower-priority subjects are processed more efficiently, optimizing overall target capture efficiency without losing essential subject feature information
Solution Approach 2:
The system changes processing parameters dynamically based on subject category and capture frequency. Subjects are classified into categories with different imaging parameters, and capture frequencies adjust prioritization weights, enabling efficient target capture while preserving necessary subject information through adaptive parameter selection
3Measurement precision
If frequency analysis is performed on all captured images, then imaging accuracy is improved, but processing time increases
Solution Approach 1:
The system segments the image processing task by first detecting subject features and categorizing them, then performing frequency analysis only on categorized subjects rather than all images. This segmentation improves recognition accuracy for relevant subjects while reducing overall processing time by avoiding redundant analysis
Solution Approach 2:
The system performs frequency analysis selectively on subjects that meet certain criteria rather than analyzing all captured images. By applying partial action only where needed, the system maintains measurement precision for important subjects while significantly reducing total processing time through selective analysis
Data Source
AI summary
An imaging support device includes a processor, and a memory connected to or built in the processor, in which the processor acquires frequency information indicating a frequency of a feature of a subject included in a captured image obtained by imaging with an imaging apparatus, the feature being classified into a category based on the feature, and performs support processing of supporting the imaging with the imaging apparatus based on the frequency information.