Automated Detection Parameter Optimization for Image Processing
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Solution Overview
Problem
Existing image processing apparatuses require manual adjustment of detection parameters through trial and error to achieve desired detection results, leading to potential detection failures or false detections.
Innovation Solution
An image processing apparatus that automates the setting of detection parameters by using an object detection section, a detection rate calculation section, an objective function value calculation section, and a detection parameter search section to optimize the detection process based on predefined conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual adjustment of detection parameters is performed through trial and error, then detection accuracy can be improved, but time consumption and operational complexity increase
Solution Approach 1:
The system performs self-adjustment of detection parameters by automatically evaluating detection results and modifying parameters based on evaluation outcomes, eliminating the need for manual trial-and-error adjustment while maintaining high detection accuracy
Solution Approach 2:
The system implements a feedback mechanism where detection results are evaluated against expected outcomes, and parameter adjustments are made based on this feedback loop, enabling automatic optimization of detection accuracy without manual intervention
2Measurement precision
If manual adjustment of detection parameters is performed through trial and error, then detection accuracy can be improved, but operational complexity increases
Solution Approach 1:
The system automatically manages parameter adjustment through self-evaluation and self-modification mechanisms, reducing operational complexity from high to low while maintaining detection accuracy through automated control
3Measurement precision
If detection parameters are set with high sensitivity to prevent detection failures, then detection accuracy improves, but false detections increase
Solution Approach 1:
The system dynamically adjusts detection parameters based on real-time evaluation of detection results, adapting the sensitivity level to balance between preventing detection failures and reducing false detections, rather than using fixed high-sensitivity settings
Solution Approach 2:
The system automatically modifies detection parameters based on evaluation outcomes, changing parameters dynamically to optimize the balance between detection accuracy and false detection rate without manual intervention
Data Source
AI summary
Provided is an image processing device with which it is possible to automate the setting of a detection parameter that is suitable for obtaining a desired detection result. An image processing device is provided with: an object detection unit for detecting the image of an object from input image data using a detection parameter; a detection rate calculation unit for comparing the result of detection by the object detection unit with information that represents a desired detection result so as to calculate at least one of a non-detection rate and a false detection rate in object detection by the objection detection unit; an objective function value calculation unit for calculating the value of an objective function, the input variable of which is at least one of the non-detection rate and the false detection rate; and a detection parameter search unit for performing a search of the detection parameter by changing the value of the detection parameter and repeating object detection, calculation of at least one of the non-detection rate and the false detection rate, and calculation of the value of the objective function until the value of the objective function satisfies a prescribed condition or the number of times a search of the detection parameter is performed reaches a prescribed count.