Projector Calibration for Non-Planar Surface Image Warping
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Solution Overview
Problem
Existing methods for projecting images onto non-planar surfaces often result in distortion, and current solutions like distortion-correcting lenses are expensive and inflexible, while pre-distorting images require complex calibration procedures that are challenging, especially when the source image and surface profiles differ significantly.
Innovation Solution
A method involving projecting a calibration image with defined dots and scale points, capturing the image, and using projective mapping to determine inverse offsets, allowing for the creation of a synthetic calibration image that compensates for non-planar surfaces, enabling accurate image projection without the need for expensive lenses or complex mechanical adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If a distortion-correcting lens is placed in the optical path, then image distortion is corrected, but cost and device complexity increase
Solution Approach 1:
The patent replaces the mechanical lens-based distortion correction system with a digital image processing system. The projector projects images onto a non-planar surface, an imaging device captures the projected image, and a processor computes mapping relationships between coordinates on the non-planar surface and the imaging device to generate corrected images, eliminating the need for complex optical lenses.
2Manufacturing precision
If a distortion-correcting lens is used, then image distortion is corrected, but adaptability to different surfaces decreases
Solution Approach 1:
The patent implements a dynamic calibration system that adapts to different non-planar surfaces. The system projects calibration patterns onto the specific surface, captures the distorted patterns with an imaging device, computes the mapping relationship for that particular surface geometry, and generates corrected images tailored to that surface. This allows the same projector to adapt to various surfaces including curved screens, vehicle windshields, and irregular walls.
3Adaptability or versatility
If mechanical lens adjustment is implemented, then adaptability to different surfaces improves, but operation time and complexity increase
Solution Approach 1:
The patent implements a self-calibrating system that automatically determines the mapping relationship between the projector and the non-planar surface without requiring manual intervention. The system autonomously projects calibration patterns, captures images with the imaging device, computes the coordinate mappings, and generates the correction algorithms, eliminating the need for time-consuming manual lens adjustments.
4Measurement precision
If the calibration image is projected out to the outer edges of the display surface, then calibration accuracy improves, but distortion increases at the edges
Solution Approach 1:
The patent applies different processing strategies to different regions of the projection surface. The system divides the projection area into multiple regions and applies region-specific correction algorithms. For edge regions where distortion is more severe, the system uses the captured calibration image data to compute localized mapping relationships that account for the increased distortion, while central regions use standard mapping. This allows accurate calibration across the entire surface including edges.
Data Source
AI summary
A calibration image including dots and scale points is projected at first and second display surfaces. A location of a scale point may be modified. A location for a registration point is determined and the registration point is added to the calibration image. The projected calibration image is captured. A location of the captured registration point and locations captured scale points are identified. Captured dots that are projected onto the first display surface and their locations are identified. Each of the captured dots identified as being projected onto the first display surface are mapped to a corresponding dot of the calibration image. Dots of the calibration image that are not projected onto the first display surface are identified, locations of each of the identified dots are determined, and a synthetic dot is added to the captured image for each identified dot. The captured image may be provided as input to a process for determining one or more inverse offsets.