Grain Flake Thickness Measurement Using Image Segmentation
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Solution Overview
Problem
Existing methods for measuring grain flakes, such as soybean flakes, are non-automated and rely heavily on skilled workers, leading to inefficiencies, human errors, and process slowdowns, without accurately measuring grain flake thickness due to lack of efficient and accurate measurement systems.
Innovation Solution
A grain flake measurement system utilizing an image collection device for color segmentation and binary image edge segment topological structural analysis, combined with a pixel per millimeter ratio, to accurately measure grain flake thickness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If non-automated measurement methods are used, then skilled workers can perform measurements, but human errors increase and process efficiency decreases
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated optical measurement system. The system uses an image collection device to capture grain flake images and an acquisition unit to automatically process these images, eliminating the need for skilled workers to manually measure grain flakes. This substitution of mechanical/manual operations with automated optical-electronic systems resolves the contradiction by simultaneously improving reliability through consistent automated measurement and productivity through high-speed image processing.
Solution Approach 2:
The measurement system performs self-service by automatically capturing, processing, and analyzing grain flake images without human intervention. The acquisition unit autonomously segments images, extracts features, and calculates thickness values, enabling the system to serve itself in the measurement process. This eliminates dependence on skilled workers while maintaining high measurement accuracy and improving process efficiency.
2Productivity
If automated measurement equipment is used, then process efficiency improves, but measurement precision may be insufficient without proper image analysis methods
Solution Approach 1:
The patent applies segmentation by dividing the grain flake image into distinct regions based on color and intensity variations. The acquisition unit segments the collected image to identify the grain flake boundaries and internal structure, enabling precise thickness measurement. This segmentation approach maintains high measurement precision while allowing automated high-speed processing, thus resolving the contradiction between productivity and measurement precision.
Solution Approach 2:
The system changes measurement parameters by using multiple image processing techniques including color segmentation, binary image conversion, and edge detection. These parameter transformations enable the automated system to extract accurate thickness information from images, ensuring measurement precision is not compromised while achieving high processing efficiency through automated computation.
3Device complexity
If simple image collection is used, then device complexity is reduced, but measurement accuracy is insufficient without advanced image processing
Solution Approach 1:
The patent introduces an acquisition unit as an intermediary between the image collection device and the measurement output. This intermediary component performs color segmentation, binary image conversion, and edge detection to bridge the simple image collection and accurate thickness measurement. The intermediary processing layer enables high measurement precision while keeping the overall device structure relatively simple and modular.
4Ease of operation
If manual measurement by skilled workers is used, then measurement can be performed, but human errors and process slowdowns increase
Solution Approach 1:
The patent replaces manual measurement operations with automated image-based measurement. The system maintains ease of operation by simply requiring grain flake samples to be placed on a substrate, while the automated acquisition and processing eliminate human errors and ensure consistent, reliable measurements across all samples without depending on worker skill levels.
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
Enables accurate and efficient automated measurement of grain flake thickness, reducing human error and improving process efficiency.
Implementation Method 1
an image collection device (110), configured to collect an image of one of the grain flakes
Data Source
AI summary
This invention describes a measurement system (100), a measurement method, and a collection, movement, and measurement system for grains (200) run through a flaking process, in order to define the grain flake thickness. The grain flake measurement system comprises: an image collection device (110) configured to collect an image of one of the grain flakes; and an acquisition unit (120) configured to receive the of the collected grain flake image through the image collection device and perform a measurement of the grain flake thickness. The grain flake measurement method comprises the steps of: collecting (560) a grain flake image through an image collection device; and measuring (561) the grain flake thickness through the collected image. The grain flake collection, movement, and measurement system (200) comprises: a grain flake collection device (210); a measurement device (130); a movement and selection device (220); an acquisition unit (120); and a command unit (230).