Projector Guide-Image Capture for Automatic Keystone Correction
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Solution Overview
Problem
Ultra-short throw projectors face challenges in automatic keystone correction due to hardware limitations, making manual correction time-consuming and inaccurate, and existing camera-based methods struggle to accurately find screen edges and correct image distortion, especially when projecting onto walls without screens.
Innovation Solution
A projector system that projects a guide image with identifiable objects, uses a camera to capture this image, and processes the captured image to identify object locations, enabling automatic keystone correction by converting the input image based on the identified locations to correct distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual keystone correction is used, then the projector can be operated without special hardware, but it takes a lot of time and is difficult to achieve high correction performance
Solution Approach 1:
The projector performs automatic keystone correction by capturing its own projected image through an integrated camera and processing the image data to calculate correction parameters, enabling the system to self-correct without external intervention or special hardware
Solution Approach 2:
The patent replaces manual mechanical adjustment with an automatic image processing system that uses camera capture, coordinate transformation, and algorithmic calculation to achieve keystone correction, substituting physical manipulation with computational methods
2Extent of automation
If automatic keystone correction using distance sensor is used, then correction can be performed automatically, but it requires additional hardware devices and cannot achieve high accuracy in ultra-short throw projectors
Solution Approach 1:
The system captures a copy of the projected image through an integrated camera, then processes this image copy to extract geometric information and calculate correction parameters, eliminating the need for external distance sensors while maintaining high accuracy
Solution Approach 2:
The camera serves multiple functions: capturing the projected image for keystone correction, displaying test patterns, and potentially other diagnostic functions, replacing the need for specialized distance sensing hardware
3Extent of automation
If camera-based keystone correction is used, then automatic correction can be achieved, but it requires wide-angle camera of 160° or more and cannot accurately find edge boundary
Solution Approach 1:
The system projects test patterns with extended boundaries that exceed the visible projection area, allowing the camera to capture reference points and edge information even with limited field of view, eliminating the requirement for wide-angle cameras
Solution Approach 2:
The patent introduces test patterns with known geometric configurations as intermediaries between the projector and camera, enabling accurate edge detection and coordinate mapping without requiring the camera to directly observe the entire projection boundary
4Ease of manufacture
If manual keystone correction is used, then no special hardware is needed, but correction of a part of the image affects other regions and high correction performance is difficult to acquire
Solution Approach 1:
The system captures the projected image, analyzes the actual geometric distortion, calculates correction parameters based on the complete image geometry, and applies global correction that accounts for interactions between different image regions, preventing local corrections from adversely affecting other areas
Data Source
AI summary
A projector device comprises: an image projection unit for projecting a guide image including a plurality of first objects; a camera; and a processor for obtaining a captured image acquired by the camera, the captured image including a guide image projected through the image projection unit. The processor identifies first location information corresponding to a location of each of a plurality of first objects included in the obtained captured image, identifies second location information corresponding to a location of each of a plurality of second objects related to the plurality of first objects, respectively, on the basis of the obtained captured image, and acquires image correction information on the basis of the first location information and the second location information.


