Color Line Sensor Parallel Processing for Code Reading Speed
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional color line cameras face challenges in processing large amounts of data and maintaining synchrony between gray value and color image data, especially at high speeds and resolutions, leading to hardware resource overload.
Innovation Solution
A camera-based code reader utilizing a color line sensor with parallel processing channels for gray value and color channels, allowing for simultaneous zooming and processing of image data in real-time, thereby reducing dynamic power loss and achieving the necessary processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a color line sensor with multiple processing channels is used to capture both grayscale and color image data simultaneously, then the processing speed and real-time capability are improved, but the hardware resource consumption and dynamic power loss increase
Solution Approach 1:
The image sensor is divided into multiple independent processing channels (grayscale channel and color channels) that operate in parallel. Each channel processes image data independently, allowing simultaneous processing of multiple types of image data without sequential bottlenecks, thereby improving processing speed while managing power consumption through distributed processing
Solution Approach 2:
The system dynamically adjusts the operation of different processing channels based on the specific reading task requirements. The control unit can activate or deactivate specific channels (grayscale or color) depending on whether color information is needed, optimizing power consumption by avoiding unnecessary processing in inactive channels while maintaining high processing speed when channels are active
2Productivity
If multiple processing channels are used to handle large amounts of image data from color and grayscale channels, then the data processing capability is improved, but the hardware resource overload increases
Solution Approach 1:
The system segments image data processing into distinct parallel channels (grayscale and color) that can be independently managed. This segmentation allows the control unit to selectively activate only the necessary channels for each specific task, improving data processing capability while avoiding the hardware resource overload that would result from continuously operating all channels at full capacity
Solution Approach 2:
The image sensor is designed with multi-functional capability to capture both grayscale and color image data using the same physical sensor array. The sensor can operate in different modes (grayscale-only, color-only, or both simultaneously) depending on the reading task requirements, providing universal data processing capability without requiring separate dedicated hardware for each function, thus managing hardware resource utilization efficiently
3Measurement precision
If grayscale image data is used for code reading, then the signal-to-noise ratio is improved, but the ability to detect and distinguish code-bearing objects from background is reduced
Solution Approach 1:
The system merges the advantages of both grayscale and color imaging by combining grayscale channels (for high signal-to-noise ratio) and color channels (for object detection and background distinction) into a unified processing framework. The control unit can selectively combine data from both channel types to achieve both high measurement precision and effective object detection simultaneously
Solution Approach 2:
The control unit acts as an intermediary that processes and integrates data from both grayscale and color channels. It can use color channel data to identify and segment code-bearing objects from the background, then apply high-precision grayscale data to the identified regions for accurate code reading, thereby mediating between the two different data types to achieve both objectives
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 solution enables efficient real-time processing of image data, maintaining high processing speed while reducing dynamic power loss, thus overcoming the limitations of conventional systems in handling large data volumes and ensuring data synchrony.
Implementation Method 1
an image sensor or line sensor records a grayscale image or a color image line by line
Data Source
Figure 1~2
Figure 3~6
Figure 7~8
AI summary
A camera-based code reader (10) for reading an optical code (44) on an object (40) in relative motion to the code reader (10) is described. The code reader (10) comprises a line-shaped image sensor (18) for capturing each image line and a control and evaluation unit (24, 25, 26) with at least one first preprocessing unit (24) and a further processing unit (25). The first preprocessing unit (24) is at least indirectly connected to the image sensor (18) and is configured to read out image line by image line during the relative motion, to rescale each image line with a zoom factor z in a preprocessing step, and then to pass it on to the further processing unit (26). The further processing unit (26) is configured to read the optical code (44) from the image lines. The image sensor (18) has several line arrays (20a-d) of light-receiving elements (22).Part of the light-receiving elements (22) is sensitive to white light, and another part of the light-receiving elements (22) is sensitive to light of only one color, thus forming a grayscale channel for receiving grayscale image lines and several color channels for receiving colored image lines. The first processing unit (24) has several parallel processing channels (50), at least one processing channel (50) for the grayscale channel and at least one processing channel (50) for each color channel, in order to rescale one grayscale image line and its associated colored image lines in parallel and synchronously.