Network Camera Infrared Cut Filter Defect Detection
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Solution Overview
Problem
It is challenging to quickly determine defects in hardware components of network cameras, such as the infrared cut filter, which affects image quality, making it difficult to identify and address issues promptly.
Innovation Solution
An information processing system that analyzes captured images from network cameras to detect defects in the infrared cut filter by comparing image quality metrics, such as pixel abnormalities, and outputs information on defects, allowing for timely notification and repair.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection methods are used to check hardware defects, then detection accuracy can be maintained, but detection time and labor costs increase significantly
Solution Approach 1:
The system enables self-diagnosis by having the network camera automatically capture images and transmit them to the server for defect detection. The server automatically analyzes the images to determine hardware defects without requiring manual inspection, thus reducing time loss while maintaining detection accuracy through automated image processing and comparison with reference images.
2Productivity
If automated image analysis is implemented, then defect detection speed increases, but system complexity and initial setup requirements increase
Solution Approach 1:
The server acts as an intermediary between the network camera and the defect analysis function. The server receives images from the camera, compares them with reference images stored in the storage unit, and determines defects automatically. This intermediary approach simplifies the overall system architecture by centralizing the complex analysis function in a separate server rather than embedding it directly in the camera device.
3Reliability
If continuous monitoring is implemented, then defect detection capability is improved, but energy consumption and data processing requirements increase
Solution Approach 1:
The system implements periodic monitoring where the network camera captures images at predetermined time intervals rather than continuously. The server compares these periodic images with reference images to detect defects. This periodic action reduces energy consumption and data processing requirements compared to continuous monitoring, while still maintaining effective defect detection capability through regular checks.
Data Source
AI summary
An aspect of the present disclosure provides an information processing system configured to process a captured image captured by an image-capturing apparatus including an infrared cut filter. In this information processing system, based on the captured image, a defect relating to the infrared cut filter is detected. Information on the defect is output.