Monitoring Camera Autofocusing via Composite Optical Filtering
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Solution Overview
Problem
Monitoring cameras struggle to maintain clear image quality and accurate autofocusing in varying visibility conditions, such as fog, dust, rainfall, and nighttime, due to limitations in existing software algorithms and methods that do not account for changing visibility statuses.
Innovation Solution
A monitoring camera system employing a composite filtering method that combines hardware optical filtering and software image filtering, using a hardware filter to block either infrared or visible light and a software filter to remove visibility obstructions, with multiple filtering levels to adapt to changing visibility conditions, ensuring clear image identification and accurate autofocusing regardless of the visibility status.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If software filtering algorithms are applied to remove visibility obstructions, then image clearness is improved, but the processing load increases and may cause delays in real-time monitoring
Solution Approach 1:
The hardware filter is positioned in the optical path before the image sensor to perform preliminary filtering of visibility obstructions. This preliminary action removes a significant portion of the filtering burden from the software algorithm, allowing real-time processing with reduced computational load while maintaining image clearness.
Solution Approach 2:
The filtering process is segmented into two stages: hardware-based optical filtering for coarse removal of visibility obstructions, and software-based digital filtering for fine-tuning image clearness. This segmentation allows each component to operate at its optimal performance level, balancing processing speed and image quality.
2Manufacturing precision
If hardware optical filtering is used to block infrared or visible light, then image quality under specific lighting conditions is improved, but the system cannot adapt to changing visibility statuses
Solution Approach 1:
The system dynamically switches between different filtering modes based on detected visibility conditions. The control unit adjusts whether the hardware filter blocks infrared or visible light, and whether software filtering is applied, according to real-time visibility status. This dynamic adaptation allows the system to maintain optimal image quality across varying environmental conditions.
Solution Approach 2:
The hardware filter is designed with multi-functionality to block either infrared or visible light bands depending on conditions. Combined with the software filter that can process various types of visibility obstructions, the system achieves universal applicability across different weather and lighting scenarios while maintaining high image quality.
3Measurement precision
If active autofocusing method is used to adjust focus in low visibility conditions, then focus accuracy is improved, but the method fails when obstacles such as windows are present
Solution Approach 1:
The hardware and software filters act as intermediaries that process the light before it reaches the image sensor. By removing visibility obstructions and optimizing the light spectrum, these filters enhance the quality of reflected light from the subject, enabling the manual autofocusing method to achieve accurate focus even through obstacles like windows by analyzing the filtered image data.
Solution Approach 2:
The system changes the parameters of light reaching the sensor by selectively blocking certain wavelengths through the hardware filter and applying software-based spectral adjustments. This parameter modification of the light signal improves the contrast and clarity of reflected light, allowing focus detection algorithms to accurately identify the subject even when obstacles are present in the optical path.
4Measurement precision
If manual autofocusing method is used to focus through obstacles, then focus accuracy is improved, but the method cannot determine focus when image sharpness is low due to bad visibility
Solution Approach 1:
The hardware and software filters perform preliminary enhancement of image sharpness by removing visibility obstructions before the autofocusing algorithm processes the image. This preliminary action improves the quality of reflected light analysis, enabling the manual autofocusing method to accurately determine focus even in previously unfavorable visibility conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides consistently clear images and accurate autofocusing across different visibility conditions, improving image quality and reducing the load on image filtering, even in low-performance devices, without compromising image compression and decompression processes.
Implementation Method 1
a hardware filter that blocks any one of an infrared light band and a visible light band of light passing through the lens unit and allows the other one to pass therethrough
Implementation Method 2
an image sensor that converts the light passing through the hardware filter into an electrical signal
Data Source
AI summary
The present invention relates to a monitoring camera having an autofocusing function based on a composite filtering robust against a change in visibility status and a video monitoring system employing the same. The present invention comprises: a hardware filter for blocking one of a visible light band and an infrared light band and allowing the other thereof to pass therethrough; and a software filter for filtering a color image or a black-and-white image generated by an image signal processor (ISP) by removing, from the color image or the black-and-white image, a factor reducing a visibility distance at the front side of a lens part, wherein the filtering band of the hardware filter and whether to perform filtering by the software filter are controlled according to a filtering level corresponding to a current visibility status at the front side of the lens part among a plurality of filtering levels. Therefore, the present invention can provide an image which is always clear enough to enable a target object to be identified regardless of a visibility status at the front of a monitoring camera, and an accurate autofocusing function can be provided constantly regardless of the visibility status in front of the monitoring camera by performing autofocusing using analysis of an image provided through stepwise composite filtering.