Physical Item Composite Imaging with Multi-Position Glare Reduction
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Solution Overview
Problem
Converting physical photographs into electronic images is challenging due to glare and image quality issues, such as missing detail in portions with glare, which are difficult to address in existing methods.
Innovation Solution
A method involving capturing a first image of a physical item, detecting its borders, generating an overlay with objects, and capturing subsequent images from different camera positions while displaying an overlay that remains fixed, allowing for pixel value correspondence and generating a composite image to reduce glare and blur.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single image is captured from a fixed camera position, then the capture process is simple and quick, but glare and artifacts appear in the image reducing quality
Solution Approach 1:
The system dynamically captures images from multiple camera positions around the physical item rather than using a fixed position. The camera moves to different locations (e.g., front, back, left, right, top, bottom) to capture the item from multiple angles, eliminating glare and artifacts by avoiding direct light reflection paths.
Solution Approach 2:
The system transitions from two-dimensional single-point capture to three-dimensional multi-point capture by positioning the camera at multiple spatial locations around the physical item. This spatial dimensionality change allows capturing the same object from different perspectives, enabling selection of optimal images without glare.
2Manufacturing precision
If multiple images are captured from different positions, then glare and artifacts are reduced, but the capture process becomes more complex and time-consuming
Solution Approach 1:
The system automatically determines camera positions, captures images, and selects the best images without requiring manual intervention. The processor automatically analyzes captured images to identify those without glare or artifacts, and autonomously generates the composite image, making the complex multi-position capture process as simple as placing the physical item on a flat surface.
Solution Approach 2:
The system uses feedback mechanisms where the processor analyzes each captured image to detect glare and artifacts, then uses this information to select optimal images for the composite. The system receives feedback from image quality analysis and adjusts its selection process accordingly, ensuring high-quality output without manual quality control.
3Manufacturing precision
If multiple images are captured from different positions, then glare and artifacts are reduced, but the capture process takes more time
Solution Approach 1:
The system captures a predetermined number of images from multiple positions (excessive action) to ensure sufficient material for creating a high-quality composite image. By capturing more images than strictly necessary (e.g., 6 positions instead of 1), the system ensures that at least some images will be free from glare and artifacts, allowing automatic selection of optimal images.
Solution Approach 2:
The system pre-determines the camera positions and capture sequence before actually capturing images. The processor automatically plans the capture path and selects which positions to capture from in advance, eliminating the need for manual positioning decisions during capture and reducing overall process time.
4Device complexity
If a single image is used for conversion, then the process is simple, but the electronic image lacks detail and quality
Solution Approach 1:
The system merges multiple captured images into a single composite image by combining the best portions from each source image. The processor analyzes multiple images and selectively combines pixel data to create a composite that contains more complete information and detail than any single source image, effectively merging the useful information from multiple perspectives.
Solution Approach 2:
The composite image functions as a composite of multiple source images, where different regions of the final image are derived from different source images. This composite approach ensures that each region of the physical item is represented by the highest quality capture, creating an electronic image with complete detail and no glare or artifacts.
Data Source
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AI summary
A computer-implemented method includes capturing, with a camera, a first image of a physical item at a first camera position, detecting borders associated with the physical item, based on the first image, generating an overlay that includes a plurality of objects that are positioned within one or more of the borders associated with the physical item, capturing, with the camera, subsequent images of the physical item, where each subsequent image is captured with a respective subsequent camera position, and during capture of the subsequent images, displaying an image preview that includes the overlay. The method further includes establishing correspondence between pixels of the first image and pixels of each of the subsequent images and generating a composite image of the physical item, where each pixel value of the composite image is based on corresponding pixel values of the first image and the subsequent images.