Yaw Error Correction in Image Stitching
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Solution Overview
Problem
Existing systems fail to accurately detect yaw error in images for planograms, leading to distortion and inefficiencies in product recognition, as internal accelerometers are ineffective in distinguishing yaw rotations and existing image stitching techniques introduce artifacts.
Innovation Solution
A system and method for camera pose yaw error determination, involving line detection, parameterization, and correction, which computes a yaw angle and presents a yaw indicator on a user interface to guide the user in capturing images, ensuring accurate alignment and minimizing distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If internal accelerometers are used to detect yaw error tilt, then device complexity is reduced, but measurement precision deteriorates because accelerometers report the same value for every angle of yaw rotation
Solution Approach 1:
The patent replaces the mechanical accelerometer-based yaw detection system with a computer vision-based line detection system. Instead of relying on physical sensors that cannot distinguish yaw rotations, the system uses image processing to detect lines in the captured images and compute yaw angles from line parameters, achieving accurate yaw measurement without mechanical sensors.
Solution Approach 2:
The patent introduces line detection and line parameterization as an intermediary between image capture and yaw angle computation. By detecting lines in the image and analyzing their parameters (slope, position), the system creates an intermediate representation that enables accurate yaw angle calculation, bridging the gap between visual data and rotational orientation.
2Productivity
If image stitching techniques are used to recognize multiple products, then productivity is improved, but manufacturing precision deteriorates due to artifacts introduced by stitching
Solution Approach 1:
The patent applies preliminary yaw correction to individual images before they are stitched together. By computing the yaw angle for each image and correcting it in advance, the system prevents yaw-related misalignments and artifacts from occurring during the stitching process, ensuring high precision in the final stitched image while maintaining efficient batch processing capability.
Solution Approach 2:
The patent applies preliminary anti-action by correcting yaw errors in each image before stitching. The system computes yaw angles and applies corrective transformations to counteract potential stitching artifacts caused by yaw misalignment, preventing the harmful effect rather than correcting it after stitching occurs.
3Manufacturing precision
If yaw correction is applied to preview images, then manufacturing precision is improved, but use of energy increases due to additional processing
Solution Approach 1:
The patent applies partial action by performing yaw correction selectively on preview images that require it, rather than processing all images uniformly. The system computes yaw angles and applies correction only when necessary to achieve the desired alignment precision, avoiding unnecessary processing energy consumption while maintaining manufacturing precision where needed.
Data Source
AI summary
A system and method that calculates a yaw error in an image and provides a user interface to a user for correcting the yaw error. The method includes receiving an image, performing line detection in the image, computing a line parameterization for lines in the image, computing a yaw angle for the image and providing the yaw data calculated in the image.