Computer Vision Guided Display Module Analysis
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Solution Overview
Problem
Conventional systems for identifying items on display modules in facilities are inefficient due to reliance on manual scanning, which is time-consuming, prone to human error, and costly, and they lack the ability to automatically generate high-resolution images from low-resolution bursts for accurate attribute detection.
Innovation Solution
A system and method that capture a burst of low-resolution images of a display module, detect and extract attributes such as barcodes or text from the images, align these attributes, and generate a high-resolution reconstructed image with sufficient detail for accurate detection and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual scanning is used to identify items on display modules, then association labor can be performed, but the process is time-consuming, costly, and prone to human error
Solution Approach 1:
The patent replaces the mechanical manual scanning process with an automated image processing system. A camera captures images of display modules, and computer vision algorithms automatically detect and identify items, eliminating the need for manual scanning operations while significantly reducing time consumption and human error.
Solution Approach 2:
The system enables self-service by automatically analyzing display modules without human intervention. The image processing system independently performs item detection, attribute identification, and inventory analysis, allowing the system to serve itself rather than requiring manual scanning operations.
2Measurement precision
If conventional image processing is used, then basic image capture is possible, but high-resolution reconstructed images cannot be generated from low-resolution bursts
Solution Approach 1:
The system performs preliminary actions by capturing multiple low-resolution images in rapid succession before processing them. These pre-captured images serve as input data for subsequent reconstruction, allowing the system to generate high-resolution output from initially low-resolution input without requiring complex high-resolution capture hardware.
Solution Approach 2:
The patent transitions from two-dimensional low-resolution images to three-dimensional spatial information through reconstruction. By processing multiple images and generating a reconstructed three-dimensional representation, the system achieves high-resolution attribute detection while managing computational complexity through structured processing approaches.
Data Source
AI summary
Devices and methods for computer vision guided analysis of a display module are disclosed herein. The method captures a burst of images of at least a portion of an object for displaying at least one item. The method detects at least one attribute of the object present in a first image of the burst of images and extracts the at least one attribute of the object present in the first image from each image of the burst of images. The method aligns the extracted at least one attribute from each image of the burst of images with the extracted at least one attribute of the first image and generates a reconstructed image based on the aligned at least one attribute of the burst of images where the resolution of the first image is different from the resolution of the reconstructed image.