Image Processing Apparatus for Accurate Meter Detection
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Solution Overview
Problem
Image processing systems struggle to accurately detect targets in photographs, particularly when occlusion or halation occurs, leading to incomplete or incorrect detection of pointers in analog meters.
Innovation Solution
An image processing apparatus with a hardware processor and memory that acquires images, detects targets, and instructs re-photographing by analyzing the image for occlusion or halation, using binarization processing and arrow icons to guide camera adjustments for improved detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the camera photographs the detection target in a state where pointers overlap, then the photographing process is simple and fast, but the detection accuracy deteriorates due to occlusion
Solution Approach 1:
The system detects the detection target from the photographed image, then provides feedback by instructing re-photographing when detection fails. This feedback loop ensures that poor quality images (with occlusion or halation) are identified and retaken, resolving the contradiction between fast photographing and accurate detection.
2Ease of operation
If the camera photographs under strong lighting conditions, then the photographing process is straightforward, but detection accuracy deteriorates due to halation
Solution Approach 1:
The system maintains ease of operation by allowing straightforward photographing under various lighting conditions, then uses detection feedback to identify images affected by halation. When halation is detected, the system instructs re-photographing, thus maintaining operational simplicity while ensuring detection accuracy.
3Measurement precision
If the system performs detailed analysis to detect occlusion and halation, then detection accuracy improves, but the processing complexity increases
Solution Approach 1:
The system performs self-service by automatically analyzing the photographed image for occlusion and halation, then self-correcting by instructing re-photographing when issues are detected. This automated self-service approach improves detection accuracy without requiring complex external intervention or manual analysis.
4Measurement precision
If the system instructs re-photographing multiple times, then detection accuracy improves, but the time consumption increases
Solution Approach 1:
The system uses feedback control to instruct re-photographing only when detection fails, not continuously. By monitoring detection results and providing targeted feedback for re-photographing only when necessary, the system improves detection accuracy while minimizing time loss from unnecessary re-photographing instructions.
Data Source
AI summary
According to one embodiment, an image processing apparatus includes a memory and a hardware processor in communication with the memory. The hardware processor is acquire an image obtained by photographing at least one detection target, detect the detection target from the image obtained, and instruct re-photographing of the detection target based on a result of the detection target.