Target Region Localization Using Stable Feature Points
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Solution Overview
Problem
Existing image processing methods struggle with accurately locating target regions due to noise and varying environmental conditions, leading to inefficiencies and reduced accuracy in identifying the target region.
Innovation Solution
The method involves dividing the target object into a stably imaged first section and an unstably imaged second section, extracting coordinates of feature points from the first section, and using these coordinates to locate the target region, even in images with incomplete features, by employing a trained feature point recognition model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing methods are used to locate target regions, then the process can be performed with simple algorithms, but the accuracy is reduced due to noise and environmental variations affecting target region identification
Solution Approach 1:
The patent segments the image processing task into multiple stages: candidate region generation, feature extraction, and target region determination. By dividing the processing into discrete steps with intermediate filtering, the system can eliminate noise at each stage rather than being affected by it throughout the entire process, thereby improving location accuracy while maintaining computational feasibility
Solution Approach 2:
The patent performs preliminary actions by generating candidate target regions and extracting features before final target region determination. This preliminary processing allows the system to pre-filter and pre-analyze multiple potential regions, identifying and eliminating false positives due to noise before committing to the final location, thus improving accuracy without requiring complex real-time processing
2Measurement precision
If comprehensive image analysis is performed to ensure accurate target region identification, then the accuracy improves, but the processing time and computational resources increase
Solution Approach 1:
The patent segments the image into multiple candidate regions and processes them independently through feature extraction and evaluation. This segmentation allows parallel processing of multiple regions, reducing the overall processing time compared to analyzing the entire image sequentially, while still maintaining comprehensive analysis for accurate identification
Solution Approach 2:
The patent extracts only the essential features needed for target region identification from candidate regions, rather than performing exhaustive analysis of all image data. By focusing computational resources on extracting and evaluating only the most discriminative features, the system achieves accurate location with reduced processing time and computational overhead
Data Source
AI summary
Some embodiments of this application disclose a method and device for locating a target region on an image, and a computer-readable storage medium. The method includes: obtaining coordinates of target points in a to-be-detected image based on a feature point recognition model; and locating the target region based on the coordinates of the target points. The to-be-detected image includes an unstably imaged target region. A target object in the target region includes a stably imaged first section and an unstably imaged second section. The target points include a feature point on the first section. The method can improve accuracy and efficiency of locating the target region.