Image Stitching Object Replacement at Stitch Lines
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Solution Overview
Problem
Conventional image stitching techniques often result in abnormal object displays when objects are positioned on the stitching line between multiple images captured by cameras with different angles and distances, leading to potential incorrect user judgments.
Innovation Solution
An image stitching processing method and system that scales and stitches images from multiple camera modules, determines object proximity to the stitching line, calculates identification confidence values, and replaces distorted object images with standard images when confidence values are below a threshold to ensure accurate representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple images from camera modules at different distances are stitched together, then the field of view is expanded, but objects on the stitching line become abnormally displayed
Solution Approach 1:
The system performs preliminary actions by detecting objects near the stitching line before stitching occurs, calculates their identification confidence values, and prepares replacement images in advance. This allows the system to proactively handle potential stitching issues rather than reacting after the fact.
Solution Approach 2:
The stitching line acts as an intermediary element between multiple camera views. The system identifies this critical boundary region and applies special processing (object detection, confidence calculation, and image replacement) to objects near this intermediary zone, ensuring seamless transitions while maintaining object integrity.
2Productivity
If image stitching is performed without object detection, then processing speed is maintained, but object representation accuracy deteriorates
Solution Approach 1:
The system applies different processing qualities to different regions of the image. Objects far from the stitching line receive standard stitching processing, while objects near the stitching line undergo enhanced detection and verification. This localized quality adjustment maintains overall processing efficiency while improving critical regions.
Solution Approach 2:
The system changes processing parameters dynamically based on object location. When an object is detected near the stitching line, the identification confidence value threshold is applied, and replacement images are generated. This parameter change approach ensures accurate object representation only where necessary, preserving processing speed for the majority of the image.
3Reliability
If identification confidence thresholding is applied to all objects, then object accuracy improves, but processing complexity increases
Solution Approach 1:
The system segments the image processing task by spatial location, dividing objects into two categories: those near the stitching line and those far from it. Only the former group undergoes complex identification confidence calculation and potential replacement. This segmentation reduces overall processing complexity while maintaining high reliability for critical objects.
Data Source
AI summary
An image stitching processing method includes: obtaining a first image taken by a first camera module, wherein the first camera module has a first distance from a reference plane; obtaining a second image taken by a second camera module, wherein the second camera module has a second distance from the reference plane; scaling the second image according to a predetermined ratio and stitching the scaled second image with the first image to obtain a third image, wherein the third image has a stitching line between the first image and the scaled second image; determining whether an object image corresponding to an object in the third image is close to or located on the stitching line; identifying the object image to generate an identification confidence value; covering a standard object image on the object image to generate a modified third image; and outputting and displaying the modified third image.