Image Processing Subject Detection with Reliability Prioritization
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Solution Overview
Problem
Existing image processing systems face challenges in accurately detecting a main subject when multiple detection results from different dictionaries exist for the same subject, leading to inconsistencies and reduced detection reliability.
Innovation Solution
An image processing apparatus equipped with a subject detection unit, detection reliability calculation unit, and main subject determination unit that prioritizes subjects based on detection reliability and user settings, allowing for accurate identification of a main subject even in regions with multiple detection results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple dictionaries are used to detect subject types, then detection coverage and versatility are improved, but detection reliability and consistency deteriorate when multiple detection results exist for the same subject
Solution Approach 1:
The patent changes the parameter of detection reliability by introducing a reliability calculation unit that computes reliability scores for each detection result. When multiple dictionaries detect the same subject, the system adjusts the detection outcome based on calculated reliability parameters, thereby maintaining versatility while improving consistency.
Solution Approach 2:
The patent implements feedback by calculating detection reliability based on the results from multiple dictionaries and using this reliability information to determine the final main subject. This feedback loop ensures that when multiple detection results exist, the system can resolve inconsistencies by prioritizing more reliable detections.
2Quantity of substance
If detection results from multiple dictionaries are combined, then the number of detected subjects increases, but inconsistencies and conflicts in detection results increase
Solution Approach 1:
The patent merges detection results from multiple dictionaries by combining them in a unified detection result storage unit. The main subject determination unit then integrates these results, resolving conflicts and inconsistencies to produce a coherent final detection output that maintains quantity while managing complexity.
Solution Approach 2:
The system manages complexity by introducing reliability as a new parameter that quantifies the quality of detection results. This parameter allows the system to handle multiple detection results systematically, prioritizing high-reliability detections and resolving conflicts based on reliability scores rather than simply accumulating all results.
3Ease of operation
If automatic main subject determination is implemented, then ease of operation is improved, but detection accuracy deteriorates when multiple detection results exist in the same region
Solution Approach 1:
The patent implements feedback-based automatic determination where the main subject determination unit receives detection results and reliability information, processes them automatically, and outputs a determined main subject. This feedback loop enables automatic operation while maintaining accuracy by using reliability calculations to guide the determination process.
Solution Approach 2:
The system improves automatic determination accuracy by introducing reliability as a decision-making parameter. Instead of making arbitrary automatic selections, the system uses calculated reliability scores to automatically determine the main subject, thereby achieving both ease of operation and measurement precision.
Data Source
AI summary
In a case where a plurality of detection results by a plurality of dictionaries exists for the same subject, a subject type may not be correctly selected. An image processing apparatus includes a subject detection unit configured to detect a plurality of types of subjects for an input image, a detection reliability calculation unit configured to calculate detection reliability for the detected subjects, a priority subject setting unit configured to set the type of a subject as a priority subject, and a main subject determination unit configured to determine a detection result as a main subject from among the detected subjects based on the set priority subject and the detection reliability. the main subject determination unit determines one subject type in the same region based on the set priority subject, the detection reliability, and the types of the detected subjects.