QR Code Recognition via Luminosity Histogram Analysis
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Solution Overview
Problem
Conventional QR code recognition methods require users to manually adjust the distance and control the size of QR codes within a recognition frame, making it inconvenient to recognize single or multiple QR codes efficiently.
Innovation Solution
An apparatus and method that automatically recognize QR codes by photographing them using a smartphone, involving a photographing unit, QR code recognition unit, display unit, memory unit, and communication unit, which convert images into grayscale, extract luminosity-concentration-level pixels, search for recognition points, and read out information, allowing for automatic recognition without distance control and simultaneous recognition of multiple codes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a conventional QR code scanner is used, then the QR code can be recognized, but the user has to manually adjust the distance and control the QR code size within a recognition frame
Solution Approach 1:
The system performs automatic distance adjustment and QR code positioning without user intervention. The controller automatically controls the movement of the photographing unit to capture the QR code at the optimal distance, eliminating the need for manual distance control by the user.
Solution Approach 2:
The patent replaces manual mechanical adjustment with an automated control system. The controller uses image processing and recognition algorithms to automatically determine the QR code's position and adjust the photographing distance, substituting human operation with automated mechanical control.
2Ease of operation
If multiple QR codes are scanned individually, then each QR code can be recognized, but the user has to perform processes one by one and manage information separately
Solution Approach 1:
The system merges multiple QR code scanning operations into a single photographing process. The controller captures an image containing multiple QR codes simultaneously and processes them together, eliminating the need for sequential scanning and improving productivity.
Solution Approach 2:
The photographing unit and controller are designed to handle both single and multiple QR codes with the same operational process. The system universally processes any number of QR codes in a single image, providing multi-functionality without requiring different procedures.
3Measurement precision
If the user brings the scanner close to the QR code for recognition, then the recognition accuracy improves, but the user loses the ability to capture surrounding context
Solution Approach 1:
The system segments the image processing task into two stages: first, automatic recognition of the QR code at any distance to ensure accuracy; second, extraction and processing of surrounding context information. This segmentation allows both precise QR code recognition and context capture without compromising either function.
Data Source
AI summary
An apparatus and method for automatically recognizing a QR code without a need to control the distance for recognition in relation to one QR code or two or more QR codes. The apparatus includes a photographing unit obtaining a surrounding image the QR code including recognition points and surroundings, a QR code recognition unit converting the surrounding image into a grayscale image of a pixel unit, converting the grayscale image into a histogram indicative of a distribution map according to the luminosity of each pixel, extracting only pixels having a luminosity value concentration level corresponding to a threshold or higher based on the histogram, setting the extracted pixels as a candidate pixel group, searching the set candidate pixel group for recognition points through a recognition marker, when the recognition points are conceived, recognizing a region in which the conceived recognition points are placed as a QR code.