Digital Map Update via Image-Based Local Identifier Extraction
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Solution Overview
Problem
Existing digital maps often lack reliable and up-to-date street names and local information, which can be time-consuming and prone to errors, especially when relying on human intervention or manual data entry.
Innovation Solution
A method and apparatus that extract local identifiers from images using pattern recognition and associate them with positional data, allowing for automatic updating of digital maps by linking extracted street names with GPS coordinates, enabling the creation of accurate and dynamic street name information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual data entry or human intervention is used to obtain street names and local information, then the data can be obtained with some level of accuracy, but the process is time-consuming and prone to errors
Solution Approach 1:
The patent replaces manual mechanical data entry processes with automated image recognition and processing systems. Cameras capture images of street signs and local identifiers, which are then automatically processed through pattern recognition algorithms to extract text and associate it with GPS coordinates, eliminating the need for manual typing and reducing human error while significantly reducing data collection time
Solution Approach 2:
The system enables automatic self-updating of digital maps by capturing images, extracting local identifiers, and associating them with positional data without requiring human operators. The apparatus autonomously performs the complete workflow from image capture to data association, allowing the mapping system to maintain itself through automated processes
2Productivity
If automated image recognition is used to extract local identifiers, then data collection speed increases and manual intervention is reduced, but the complexity of the system increases
Solution Approach 1:
The apparatus is designed as a multi-functional integrated system that combines GPS reception, image capture, pattern recognition, text extraction, and data association capabilities within a single device. This universal approach allows one system to perform multiple functions that would otherwise require separate devices or processes, managing complexity through consolidation rather than proliferation of components
Solution Approach 2:
The patent introduces an intermediary processing layer that bridges image capture and digital map updates. The pattern recognition module serves as an intermediary that translates visual information from images into structured text data, which is then associated with positional data. This intermediary layer simplifies the overall system architecture by creating clear separation between data acquisition and data integration functions
Data Source
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Figure 3a~3b
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AI summary
A method comprises extracting a local identifier (130, 730a, 730b) from an image (100, 500, 700), the image (100, 500, 700) also having positional data (120) relating to the location at which the image (100, 500, 700) was captured; and associating the extracted local identifier (130, 730a, 730b) with the corresponding positional data (120) to allow for associating the extracted local identifier with a digital map (300, 600, 800).