Optoelectronic Code Reading with Local Brightness Adaptation
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Solution Overview
Problem
Existing code reading technologies face challenges in efficiently processing large image data under real-time conditions, particularly in handling varying brightness levels and orientations, which can lead to difficulties in segmenting and reading optical codes.
Innovation Solution
A method for reading optical codes that involves a computer-implemented process using a code reader or processing unit. The method records an image section-wise or row-wise and performs a first brightness adaptation locally within the image. This adaptation allows for the localization of regions of interest containing optical codes, which are then processed using a decoder. The method optimally combines segmentation and brightness adaptation, enabling intelligent contrast spreading tailored to the region of interest.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional image processing algorithms are used for segmentation, then the processing speed is fast, but the accuracy in locating code regions under varying brightness conditions deteriorates
Solution Approach 1:
The patent applies preliminary action by performing brightness adaptation before code region localization. The system adjusts the brightness of the entire image or specific regions in advance to normalize lighting conditions, which then enables more accurate and faster code detection. This pre-processing step ensures that subsequent segmentation algorithms operate under optimal brightness conditions, resolving the contradiction between accuracy and speed.
Solution Approach 2:
The patent changes the brightness parameter of the image by applying adaptive brightness adjustment algorithms. By modifying the brightness values dynamically based on the captured image's lighting conditions, the system creates optimized image data for code detection. This parameter transformation enables both accurate localization and maintains processing efficiency by preparing the data in advance.
2Reliability
If brightness adaptation is performed on the entire image, then the code readability is improved, but the processing time and data volume increase
Solution Approach 1:
The patent segments the image into multiple regions or blocks before applying brightness adaptation. Instead of processing the entire image uniformly, the system divides it into smaller manageable sections and applies brightness adjustment only where necessary. This segmentation approach reduces the total processing time and data volume while maintaining code readability in the regions containing codes.
Solution Approach 2:
The patent applies local quality by performing brightness adaptation selectively on specific regions of the image rather than the entire image. The system identifies regions where codes are likely present and applies brightness adjustment only to those areas. This localized approach improves code readability in relevant regions while minimizing processing time and computational resources spent on areas without codes.
3Adaptability or versatility
If multiple code readers are provided at a reading tunnel, then the coverage of different orientations is improved, but the device complexity and cost increase
Solution Approach 1:
The patent makes the single code reader universal by enabling it to detect codes of various orientations through software-based brightness adaptation and image processing algorithms. Instead of requiring multiple physical readers for different orientations, the system uses a single reader that can adapt its processing to handle codes regardless of their orientation, thereby reducing device complexity while maintaining versatility.
Solution Approach 2:
The patent replaces the mechanical approach of using multiple physical code readers with different orientations with a software-based image processing system. By using algorithms that can dynamically adjust brightness and detect codes in various orientations through software processing, the system eliminates the need for multiple hardware readers, reducing device complexity while achieving the same orientation coverage.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The proposed method enhances the reading of optical codes by allowing for optimal combination of segmentation and brightness adaptation, effectively addressing the challenges of varying brightness levels and orientations. This results in improved code readability, even under difficult conditions such as extremely bright or dark images.
Implementation Method 1
A camera based code reader records images of the objects having the codes located thereon by means of an image sensor
Implementation Method 2
a first brightness adaptation of the image is carried out
Data Source
AI summary
A method of reading an optical code is provided in which an image having the code is recorded, a first brightness adaptation of the image is carried out, a region of interest having the optical code is localized in the image, and the optical code in the region of interest is read. In this respect, the first brightness adaptation is a local brightness adaptation that is carried out in partial regions of the image still while further sections of the image are read; and the localization of the region of interest is based on image information of the image already processed by the first brightness adaptation.