Object Identification Device for Slight Image Differences
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing object identification methods using local feature quantities struggle with accurately distinguishing between images showing objects with slight differences, leading to false identifications.
Innovation Solution
A device and method that calculate geometric transformation information to match local feature quantities between input and reference images, allowing for the identification of different areas and extraction of feature quantities from these areas to improve matching accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If local feature quantity matching is performed on entire images, then identification robustness against size and angle changes is improved, but identification accuracy deteriorates when objects have slight differences
Solution Approach 1:
The patent divides the image into multiple local areas and performs feature quantity extraction and matching only in specific local areas rather than the entire image. This segmentation allows the system to focus on distinctive regions that contain objects with slight differences, thereby improving identification accuracy while maintaining robustness through geometric transformation information.
Solution Approach 2:
The patent applies different processing strategies to different local areas of the image. By identifying and focusing on local areas that contain objects with slight differences, the system enhances the quality of matching in critical regions while using geometric transformation information to maintain overall robustness against size and angle changes.
2Area of stationary object
If feature points are densely distributed, then coverage of the object is improved, but computational complexity increases
Solution Approach 1:
The patent extracts and processes only the necessary local areas that contain objects with slight differences, rather than processing all feature points in the entire image. This extraction approach reduces computational complexity by eliminating unnecessary calculations in regions that do not contribute to distinguishing objects with slight differences.
Solution Approach 2:
The patent performs feature matching on a partial basis by focusing only on specific local areas rather than the entire image. This partial action approach reduces computational complexity while still achieving adequate coverage of critical regions that contain objects with slight differences.
Data Source
AI summary
Disclosed is an object identification device and the like for reducing identification error in a reference image which presents an object that is only slightly difference from an object presented in an input image. The object identification device includes a local feature quantity matching unit for calculating geometric transformation information for transformation from a coordinate in a reference image to a corresponding coordinate in an input image, and matching a local feature quantity extracted from the reference image and a local feature quantity extracted from the input image, an input image different area determination unit for transforming the different area in the reference image on a basis of the geometric transformation information about the input image determined to be in conformity by the matching, and determining a different area in the input image corresponding to the different area in the reference image, an input image different area feature quantity extraction unit for correcting a different area in the input image, and extracting a feature quantity from the corrected different area of the input image, and a feature quantity matching unit for matching a feature quantity extracted by the input image different area feature quantity extraction unit and a feature quantity extracted from the different area in the reference image, and outputting a matching result.