IR Camera Displacement-Based Focusing via Visible Light Parallax
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Solution Overview
Problem
Existing IR cameras face challenges in continuously focusing their IR and visible light imaging subsystems without interrupting the imaging process, leading to potential loss of focus during active imaging due to the parallax error and angular misalignment between the optical subsystems.
Innovation Solution
An IR camera system that includes a processor to determine the object distance by analyzing the displacement between IR and visible light images, allowing for continuous focusing adjustments using a focus motor, with optional use of a laser device to enhance precision, enabling efficient and uninterrupted focusing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the focus motor is controlled to focus the IR optics by moving the lens through its whole range to determine the best focus position, then the IR optics can be focused properly, but the imaging procedure is interrupted and time is lost
Solution Approach 1:
The system uses feedback from the visible light imaging subsystem to continuously monitor and adjust the IR optics focus. The processor compares the position of objects in visible light images with IR images and automatically adjusts the lens position to maintain alignment, eliminating the need for manual focus range testing and enabling continuous imaging.
Solution Approach 2:
The visible light imaging subsystem serves dual purposes: it captures visible images and simultaneously provides focus information for the IR optics. The system self-adjusts by using its own imaging data to control the IR lens, eliminating the need for separate focus calibration procedures.
2Adaptability or versatility
If the IR and visual optical subsystems are placed at a distance from each other to accommodate both imaging functions, then both imaging capabilities are achieved, but parallax error causes displacement between images
Solution Approach 1:
The processor continuously monitors the relative positions of objects in both IR and visible light images and uses this feedback to calculate and apply corrective transformations. This real-time alignment compensation eliminates parallax errors despite the physical separation of the optical subsystems.
Solution Approach 2:
Instead of mechanically aligning the optical subsystems physically, the system uses software-based image transformation and registration techniques to achieve precise alignment. The processor applies scale factors and offset corrections to align IR images with visible light images, replacing mechanical precision requirements with computational methods.
3Ease of manufacture
If the optical axes of the IR and visual optical subsystems are not perfectly parallel to simplify manufacturing, then manufacturing is easier, but angular misalignment causes displacement between images
Solution Approach 1:
The system replaces mechanical optical axis alignment with software-based image registration. The processor detects corresponding features in IR and visible light images and calculates transformation parameters to correct angular misalignment, allowing manufacturing tolerances to be much looser while maintaining registration accuracy.
Solution Approach 2:
The system dynamically adjusts image parameters (scale, rotation, translation) based on detected feature positions. By changing these software parameters rather than physical optical parameters, the system compensates for manufacturing imperfections in optical axis alignment.
4Measurement precision
If the visible light imaging subsystem has a larger field of view and higher resolution than the IR imaging subsystem, then the visible light imaging quality is improved, but image blending requires complex alignment transformations
Solution Approach 1:
The processor uses the high-resolution visible light images as a reference to guide the alignment of IR images. By detecting features in the visible light images and tracking their positions, the system automatically determines the transformation parameters needed to align the lower-resolution IR images, simplifying the overall alignment process.
Solution Approach 2:
The visible light imaging subsystem serves multiple functions: it captures visible images for display and simultaneously provides the reference framework for aligning IR images. This multi-functionality reduces overall system complexity by using one subsystem to support both imaging and alignment tasks.
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
Enables continuous and efficient focusing of IR cameras without interrupting the imaging process, maintaining focus throughout the procedure by determining the displacement between IR and visible light images and adjusting the IR optics accordingly.
Implementation Method 1
Two main factors contribute to this displacement. First, optical subsystems for IR imaging and visible light imaging are placed at a distance from each other on the camera, which causes a parallax error.
Implementation Method 2
The focus motor must be controlled according to some focusing algorithm to focus the IR optics properly. Typically this is done by moving the lens to one of its extreme positions and then sliding it through its whole range to determine the position that gives the best focus.
Data Source
AI summary
An IR camera includes a first optical subsystem for generating an IR image of an object and a second optical subsystem for generating a visual light image of the object. The IR camera further includes a focusing device for focusing the first optical subsystem. The IR camera also has a processor for determining a focus distance for focusing the first optical subsystem on the object. The processor determines the focus distance based on a displacement of a feature in the visual light image.