Customized Composite Map Image Generation via Feature Point Matching
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Solution Overview
Problem
Existing GPS navigation systems provide non-customized maps and points of interest, failing to meet the specific needs of service subscribers.
Innovation Solution
An electronic apparatus with a map database that receives user-specified input images, matches feature points with corresponding map points, and overlays the input image onto a reference map to generate a customized composite map image, adjusting for positional differences and allowing for transparency settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If standardized maps and POI are provided by telecommunication service providers and PND manufacturers, then the service coverage is broad, but the customization capability is poor and user needs cannot be satisfied
Solution Approach 1:
The system performs preliminary actions by automatically detecting feature points in user-uploaded images, matching them with corresponding map points, and pre-calculating transformation parameters before the user actually needs the customized map. This automation of preliminary customization tasks resolves the contradiction by enabling high adaptability without requiring complex manual configuration from users.
Solution Approach 2:
The system enables self-service customization where users can upload their own images and the system automatically processes them through feature point detection, matching, and overlay operations. This self-service mechanism allows the system to adapt to individual user needs (improving customization capability) without requiring complex manual intervention or system configuration (reducing perceived complexity).
2Manufacturing precision
If manual customization of map images is implemented, then the customization precision is high, but the operation complexity increases and user burden is heavy
Solution Approach 1:
The system replaces manual mechanical operations (users manually selecting and positioning map features) with automated computational processes (feature point detection algorithms and automatic image transformation). This substitution maintains high customization precision through accurate algorithmic processing while dramatically improving ease of operation, as users only need to upload images rather than manually configure numerous parameters.
Solution Approach 2:
The system introduces an intermediary automated processing layer between user input and final output. Users simply upload images, and the intermediary system automatically performs feature point detection, matching, transformation calculation, and image overlay. This intermediary process ensures high precision customization while keeping user operations simple, resolving the contradiction between precision and ease of operation.
Data Source
AI summary
A method is to be implemented by an electronic apparatus having a map database established therein, and includes the steps of: receiving a user-specified input image of an area of interest, and obtaining from the map database a reference map that encompasses the area of interest; selecting a set of feature points in the user-specified input image, and a set of map points in the reference map that correspond in geographical features to the feature points; transforming the user-specified input image according to positional differences between the feature points and the corresponding map points to thereby obtain a to-be-registered image having adjusted feature points corresponding in position to the map points; overlaying the to-be-registered image onto the reference map to thereby obtain a customized composite map image; and outputting the customized composite map image.