Object Identification via Feature Portion Imaging
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Solution Overview
Problem
Current methods for identifying object categories, particularly using images, are time-consuming and often yield inaccurate results due to broad image capture, lack of detailed information, and exclusion of key feature parts.
Innovation Solution
An object identification method that involves acquiring a first image of an object, determining a feature portion based on the first image, acquiring a second image of the feature portion, and identifying the object category based on the second image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a broad image of the object is captured, then more information is available, but the key feature parts may not be included and identification accuracy decreases
Solution Approach 1:
The patent divides the object identification process into two stages: first capturing a broad image to obtain overall information, then identifying key feature portions and capturing separate images of those specific parts. This segmentation allows the system to benefit from both comprehensive coverage and focused detail, resolving the contradiction between information completeness and identification accuracy.
Solution Approach 2:
The patent extracts key feature portions from the broad object image through automated identification, then separately captures images of only those critical features. This extraction process eliminates irrelevant background information while preserving essential identification characteristics, thereby improving accuracy without losing important information.
2Reliability
If users manually search for object category through search engines and dictionaries, then identification can be performed, but the process is time-consuming
Solution Approach 1:
The patent implements automated object identification where the system itself performs the identification task without requiring user intervention in manual searching. The system automatically captures images, identifies key features, and determines object categories, making the process self-service and eliminating time-consuming manual searches while maintaining reliable identification capability.
Solution Approach 2:
The patent replaces the mechanical process of manual searching through search engines and dictionaries with an automated image recognition system. This substitution uses computer vision and pattern recognition algorithms to automatically identify objects, dramatically reducing the time required while maintaining or improving identification reliability.
3Ease of operation
If direct category identification is performed based on captured images, then the process is simple, but results are inaccurate due to lack of detailed information
Solution Approach 1:
The patent maintains operational simplicity by automating the multi-step process. The system automatically segments the identification task into broad image capture, feature portion identification, and detailed feature imaging, executing each step without user intervention. This automated segmentation preserves ease of operation while improving accuracy through focused feature analysis.
Solution Approach 2:
The patent performs preliminary identification of key feature portions from the broad image before capturing detailed images of those features. This preliminary action guides the subsequent detailed imaging process, ensuring that critical features are captured with appropriate detail while maintaining a simple automated workflow that improves accuracy without complicating operation.
Data Source
AI summary
Provided are an object identification method, apparatus, and device. The object identification method comprises: acquiring a first image of at least part of an object; determining a feature portion of the object on the basis of the first image; acquiring a second image of the feature portion of the object; and identifying an object category of the object on the basis of the second image. According to the object identification method, apparatus, and device, in which a feature portion of an object is acquired and identification of the category of the object is performed on the basis of the feature portion, operations are simple, and the accuracy of object identification can be effectively improved.