Intelligent Image Obstacle Removal via Reference Region Repair
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Solution Overview
Problem
Current image processing methods require burdensome post-processing to remove obstacles from captured images, which is inefficient and burdensome for users.
Innovation Solution
A computer-implemented method and apparatus that automatically detects and removes obstacles from images by recognizing their shape and color differences, and repairs the erased region using reference images or background stretching, allowing for real-time obstacle removal during image capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If post-processing software is used to remove obstacles from images, then obstacle removal capability is achieved, but user operation complexity increases and processing efficiency decreases
Solution Approach 1:
The system performs automatic obstacle detection, selection, and removal without requiring user intervention in post-processing. The electronic device captures the image, automatically identifies obstacles, and removes them through the processing unit, making the system serve itself rather than requiring user operation with drawing software.
Solution Approach 2:
The obstacle removal process is performed at the time of image capture rather than in subsequent post-processing. The electronic device detects and removes obstacles during the capturing moment, eliminating the need for later manual editing operations.
2Reliability
If manual post-processing is used to remove obstacles, then obstacle removal is possible, but processing time increases
Solution Approach 1:
The system performs obstacle removal at the moment of image capture rather than in subsequent post-processing. The processing unit removes obstacles from the captured image immediately, eliminating the time loss associated with later manual editing operations.
Solution Approach 2:
The electronic device automatically detects and removes obstacles without requiring user intervention in post-processing, significantly reducing the time required for obstacle removal compared to manual methods.
3Productivity
If simple erasing is used to remove obstacles, then processing speed increases, but image realism deteriorates due to visible erasure regions
Solution Approach 1:
The system introduces a reference image as an intermediary to fill the erased obstacle region. The reference image, captured at the same location and time without obstacles, serves as a mediator to restore the erased region, maintaining both processing efficiency and image realism.
Solution Approach 2:
The system copies the background information from a reference image to replace the erased obstacle region. By copying relevant pixels from the reference image that corresponds to the same spatial location, the system restores the erased area while maintaining image realism and avoiding visible artifacts.
Data Source
Figure 1~2B
Figure 2C~2E
Figure 2F~2G
AI summary
The present disclosure relates to a method and an apparatus for intelligently capturing an image, pertaining to the field of computer technology. The method includes: acquiring (101, 201) an image captured by a camera; acquiring (102, 201) an obstacle in the image; erasing (103) information within an obstacle region which corresponds to the obstacle; and repairing (104, 204) the obstacle region in which information has been erased. With the present disclosure, it can solve the problem in the related art that the obstacle has to be removed in the post-processing of the image and the operating efficiency is low, and it can simplify the operation of the user and improve the user experience.