Projector Surface Detection Using Grid Pattern Continuity
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Solution Overview
Problem
Existing projectors struggle to accurately identify and project images onto irregular or uniquely shaped projection surfaces, especially in varying ambient illuminance conditions, leading to suboptimal image placement and quality.
Innovation Solution
An electronic device equipped with a camera and processor that analyzes a projected grid pattern on the surface, extracting features like line continuity, texture complexity, and chroma information to identify an optimal projection region, adjusting the image accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a projector projects images onto irregular or uniquely shaped projection surfaces, then the adaptability to different surfaces is improved, but the measurement precision of the projection surface and image placement accuracy deteriorate
Solution Approach 1:
The system performs preliminary actions by projecting a test pattern image containing multiple grid lines onto the projection surface before the actual image projection. The camera captures this test pattern to detect the actual shape and characteristics of the surface in advance, allowing the system to calculate accurate projection parameters before final image projection occurs
Solution Approach 2:
The system implements feedback by using the camera to capture the projected test pattern and analyzing the captured image to determine the actual projection surface characteristics. This feedback loop allows continuous adjustment and optimization of projection parameters based on real measurements from the actual surface geometry
2Ease of operation
If the projector uses automatic detection methods to identify projection surfaces, then the ease of operation is improved, but the reliability of surface identification in varying ambient illuminance conditions deteriorates
Solution Approach 1:
The test pattern image employs specific color characteristics and contrast ratios designed to be distinguishable across varying ambient illuminance conditions. By using patterns with deliberate color variations and brightness differences, the system ensures reliable detection regardless of environmental lighting, maintaining identification accuracy while preserving ease of automatic operation
3Manufacturing precision
If the system analyzes multiple feature information from captured images, then the manufacturing precision of image placement is improved, but the device complexity increases
Solution Approach 1:
The image analysis process is segmented into distinct functional components: detecting grid lines, identifying intersections, calculating geometric parameters, and determining projection surface characteristics. Each segment handles a specific aspect of the analysis independently, making the overall complex process more manageable and computationally efficient while maintaining high placement precision
Data Source
AI summary
An electronic device includes: an image projection device; a camera; a memory storing instructions; and at least one processor including a processing circuitry. The at least one processor is configured to control the image projection device to output an image including a predetermined pattern onto a projection surface, acquire a captured image of the projection surface by using the camera, identify feature information including continuity information of a line included in the predetermined pattern in the captured image, identify at least a partial region of the projection surface as an output region based on the feature information, and control the image projection device to project an input image onto the identified output region.