Click-Refined Image Annotation with Predicted Region Expansion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image annotation methods rely heavily on manual point selection and line drawing, which are inefficient and require high user accuracy, making the process cumbersome and time-consuming.
Innovation Solution
An image processing method that allows users to annotate regions by expanding and reducing a predicted region through clicks, adjusting the region until the difference between the predicted and target regions meets a threshold, using a first and second click operation to refine the annotation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual point selection and line drawing are used for image annotation, then annotation accuracy can be achieved, but the annotation process becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary action by automatically generating an initial predicted region for the target object before user interaction. This pre-computed region serves as a starting point that is already close to the final annotation, reducing the time users need to spend on manual point selection and line drawing while maintaining accuracy through subsequent refinement steps.
Solution Approach 2:
The invention replaces the mechanical manual process of point selection and line drawing with an automated algorithmic system that generates predicted regions. This substitution eliminates the time-consuming manual operations while preserving annotation accuracy through the collaborative refinement process between the system's predictions and user corrections.
2Manufacturing precision
If manual point selection and line drawing are used for image annotation, then precise region boundaries can be defined, but the operation becomes cumbersome and complex
Solution Approach 1:
The system extracts the complex task of defining region boundaries from the user and delegates it to an automated algorithm that generates the predicted region. Users only need to provide simple feedback (accept/reject or minor adjustments) rather than manually selecting points and drawing lines, thus maintaining boundary precision while dramatically simplifying the operation.
Solution Approach 2:
The predicted region acts as an intermediary between the system's automatic object detection and the user's final annotation. It provides a pre-computed boundary that users can easily accept or modify, eliminating the need for users to directly perform complex boundary definition operations while still achieving precise region boundaries.
3Measurement precision
If high user accuracy is required for manual annotation, then precise annotations can be obtained, but the difficulty and time consumption increase significantly
Solution Approach 1:
Instead of requiring users to perform complete manual point selection and line drawing operations with high precision, the system performs partial action by automatically generating the predicted region first. Users only need to perform minimal refinement actions (such as accepting the prediction or making small adjustments), which reduces both the complexity and time required while maintaining annotation precision.
Data Source
AI summary
The present disclosure provides an image processing method and apparatus, and relates to the field of image processing, and in particular to the field of image annotation. An implementation is: obtaining an image to be processed including a target region to be annotated; in response to a first click on the target region, performing a first operation to expand a predicted region for the target region based on a click position of the first click; in response to a second click in a position where the predicted region exceeds the target region, performing a second operation to reduce the predicted region based on a click position of the second click; and in response to determining that a difference between the predicted region and the target region meets a preset condition, obtaining an outline of the predicted region to annotate the target region.