Machine vision system for food grain quality evaluation: A review

P Vithu, JA Moses - Trends in food science & technology, 2016 - Elsevier
Background Quality of pre-processed food grains is a critical aspect and a major decider of
market acceptability, storage stability, processing quality, and overall consumer acceptance …

Wheat seed classification: utilizing ensemble machine learning approach

A Khatri, S Agrawal, JM Chatterjee - Scientific programming, 2022 - Wiley Online Library
Recognizing and authenticating wheat varieties is critical for quality evaluation in the grain
supply chain, particularly for methods for seed inspection. Recognition and verification of …

[PDF][PDF] Identification of rice varieties using machine learning algorithms

I Cinar, M Koklu - Journal of Agricultural Sciences, 2022 - dergipark.org.tr
Rice, which has the highest production and consumption rates worldwide, is among the
main nutrients in terms of being economical and nutritious in our country as well. Rice goes …

Automated detection of mechanical damage in flaxseeds using radiographic imaging and machine learning

M Nadimi, LG Divyanth, J Paliwal - Food and Bioprocess Technology, 2023 - Springer
The growing demand for flaxseed as a source of healthy edible oil mandates the need for
adopting novel strategies for preserving its quantity and quality. Mechanical damage during …

Sieveless particle size distribution analysis of particulate materials through computer vision

C Igathinathane, LO Pordesimo, EP Columbus… - … and Electronics in …, 2009 - Elsevier
This paper explores the inconsistency of “length-based separation” by mechanical sieving of
particulate materials with standard sieves, which is the standard method of particle size …

Image processing techniques to estimate weight and morphological parameters for selected wheat refractions

R Sharma, M Kumar, MS Alam - Scientific Reports, 2021 - nature.com
The geometric and color features of agricultural material along with related physical
properties are critical to characterize and express its physical quality. The experiments were …

Potential of artificial neural networks in varietal identification using morphometry of wheat grains

BP Dubey, SG Bhagwat, SP Shouche, JK Sainis - Biosystems engineering, 2006 - Elsevier
The shape, size and colour of grains are normally employed to identify wheat varieties. Use
of computer-based image analysis is a good alternative to visual identification. Artificial …

Major orthogonal dimensions measurement of food grains by machine vision using ImageJ

C Igathinathane, LO Pordesimo… - Food Research …, 2009 - Elsevier
A machine vision ImageJ plugin was developed in Java for orthogonal length and width
determination of singulated particles from digital images. A flatbed scanner obtained the …

GrainSpace: A large-scale dataset for fine-grained and domain-adaptive recognition of cereal grains

L Fan, Y Ding, D Fan, D Di… - Proceedings of the …, 2022 - openaccess.thecvf.com
Cereal grains are a vital part of human diets and are important commodities for people's
livelihood and international trade. Grain Appearance Inspection (GAI) serves as one of the …

[HTML][HTML] Optical signal intensity incorporated rice seed cultivar classification using optical coherence tomography

SA Saleah, SY Lee, RE Wijesinghe, J Lee… - … and Electronics in …, 2022 - Elsevier
Here, the optical signal intensity of swept-source optical coherence tomography (SS-OCT)
was incorporated to assess the images of different rice seeds for precise cultivar …