Head rice rate measurement based on concave point matching.

Area of Science:

• Agricultural Engineering
• Food Science
• Image Processing

Background:

• Head rice rate is a critical metric for assessing rice quality.
• Accurate measurement of head rice is essential for quality control in the rice industry.
• Existing methods may lack efficiency or precision for bulk grain analysis.

Purpose of the Study:

• To develop and validate a novel, automated technology for measuring the head rice rate in bulk grain.
• To enhance the accuracy and efficiency of head rice determination using image processing techniques.
• To provide a reliable method for real-time head rice rate calculation.

Main Methods:

• Utilized an inflection point detection-based technology with a vibrator and conveyor belt for bulk grain image acquisition.
• Applied the edge center mode proportion method (ECMP) for concave point matching and separation.
• Employed the minimum enclosing rectangle (MER) method for rice length calculation and head rice identification.

Main Results:

• Successfully demonstrated bulk grain image acquisition and automated head rice rate measurement.
• Achieved separation accuracy exceeding 95% for both indica and japonica rice varieties.
• Confirmed that increased rice quantity did not significantly impact ECMP and MER performance, with MER yielding a relative error less than 3%.

Conclusions:

• The developed inflection point detection technology provides a reliable and accurate method for head rice rate calculation.
• The ECMP and MER methods offer robust performance, unaffected by variations in grain quantity.
• This automated approach serves as a valuable reference for future studies in head rice quality assessment.