Grain Granulometry Imaging for Accurate Automated Measurement
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Solution Overview
Problem
Existing methods for measuring grain particle granulometry, such as cracked soybeans, rely on non-automated processes that require skilled labor, leading to inefficiencies and human errors, and lack accurate image-based analysis techniques.
Innovation Solution
A system and method utilizing an image collection device and command unit for automated and continuous grain particle granulometry measurement, employing color segmentation in the HSV space and binary image edge segment topological structural analysis to precisely measure grain contours, pixel occupation, and define pixel per milliliter ratios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If non-automated measurement methods are used, then skilled workers can perform measurements, but measurement efficiency decreases and human errors increase
Solution Approach 1:
The patent replaces manual mechanical measurement methods with an automated optical measurement system. The image collection device captures grain images, and the command unit processes these images through color segmentation and edge detection algorithms to automatically determine granulometry, eliminating the need for skilled manual measurement while improving both accuracy and efficiency.
Solution Approach 2:
The patent creates optical copies of grain particles through image collection, replacing physical manual measurement. By capturing images of grains and analyzing them through color segmentation and edge detection, the system replicates the measurement process automatically, improving productivity while maintaining precision through digital analysis rather than manual inspection.
2Productivity
If automated equipment is used, then measurement efficiency increases, but device complexity increases
Solution Approach 1:
The patent segments the measurement process into distinct functional modules: image collection device for capturing grain images, command unit for processing, color segmentation module for identifying grain regions, and edge detection module for contour analysis. This modular segmentation reduces overall system complexity by making each component independent and easier to implement while maintaining high automation efficiency.
3Measurement precision
If image collection and color segmentation are performed, then measurement precision improves, but processing time increases
Solution Approach 1:
The patent performs preliminary image collection and color segmentation before final measurement analysis. By pre-processing the images to identify grain regions and separate them from background through color segmentation, the system prepares the data in advance for rapid edge detection and granulometry calculation, reducing overall processing time while maintaining high precision through comprehensive analysis.
Data Source
AI summary
This invention describes a particle granulometry measurement system (100), a collection, movement, and measurement system (200) and a grain particle granulometry measurement method run through a cracking process in order to define their particle granulometry and analyze its functioning. The grain particle granulometry measurement system (100) comprises an image collection device (110) configured to collect images from a plurality of grains; and a command unit (120) configured to receive images from the plurality of grains collected through the image collection device (110) and perform a particle granulometry measurement of the plurality of grains. The grain collection, movement and measurement system (200) comprises: a grain collection device (210); the separator device (230); a measurement device (130); and a command unit (120). The grain particle granulometry measurement method comprises the steps of: collecting (540) an image of the plurality of grains through image collection device; and measuring (541) the particle granulometry of each grain of the plurality of grains through the collected image.


