Computer vision system for characterization of Canadian pulses

用于表征加拿大豆类的计算机视觉系统

基本信息

  • 批准号:
    RGPIN-2019-05140
  • 负责人:
  • 金额:
    $ 2.26万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2019
  • 资助国家:
    加拿大
  • 起止时间:
    2019-01-01 至 2020-12-31
  • 项目状态:
    已结题

项目摘要

Canada is the second largest producer of pulses in the world. In 2016, it exported around 6 million tonnes of pulses (more than 80% of production) valued at $ 4.2 billion to over 150 countries. At present, in the international pulse trade, around 3 out of 10 contracts results in disputes requiring arbitration between buyers and sellers, which is mainly due to differences in methodology and nomenclature in quality standards. The countries that grow and export pulse have been asked to develop innovative methods to measure and define its quality in order to strengthen certification systems.******According to Pulse Canada, delivering “Canada brand” pulses to the international market and maintaining a competitive position is an ongoing challenge. The widely varying values given to the quality parameters by importing countries severely affects Canadian farmers and traders in terms of grading, packing and certification. Therefore, an objective system for measuring the surface and internal attributes of pulses, and determining the grades based on customer specifications, is urgently required to maintain Canada's share in the international pulse market.******Computer vision (CV) is a non-destructive method in which images of an object (static or moving) are taken and analyzed to obtain the target quality objectively. In this proposed program, the CV techniques will be developed to characterize the primary quality determinants as defined by the Canadian Grain Commission (damage, degree of soundness, foreign material and mix of other pulse classes) for the top three pulses (lentils, dry peas and dry beans) in Canada. The CV system for the monochrome camera, red-green-blue (RGB) color camera, and near infrared (NIR) camera with optimized illumination, image processing, feature extraction, machine learning algorithms and classification models will be developed and tested.******The developed algorithms will be used to implement an automated online grading system for the pulse handling facilities of Canada. This will assist in ensuring the validity of the “Guaranteed Canadian Pulse” stamping in the international market. Also, the developed protocols will beneficially supplement other on-going Canadian pulse research programs such as those focused on storage (color degradation) and breeding (pattern recognitions in varietal purity).******Capacity building and knowledge dissemination: Ten HQP (1 PDF, 1 PhD, 3 MSc and 5 UG) will be trained in automated, non-destructive inspection procedures for food safety and quality. The training received in this area will be transferable to similar research or industrial applications involving other food products. A workshop will be organized for the farmers, processors and traders in the Canadian pulse sector, in order to disseminate the developed technologies.**
加拿大是世界上第二大豆类生产国。2016年,它向150多个国家出口了约600万吨豆类(占产量的80%以上),价值42亿美元。目前,在国际豆类贸易中,每10份合同中约有3份会导致买卖双方发生需要仲裁的纠纷,这主要是由于质量标准的方法和术语不同。已要求种植和出口豆类的国家制定创新方法来衡量和确定其质量,以加强认证制度。据加拿大脉冲,提供“加拿大品牌”脉冲到国际市场和保持竞争地位是一个持续的挑战。进口国对质量参数的评价差别很大,在分级、包装和认证方面严重影响了加拿大农民和贸易商。因此,迫切需要一个客观的系统来测量豆类的表面和内部属性,并根据客户的规格确定等级,以保持加拿大在国际豆类市场上的份额。计算机视觉(CV)是一种非破坏性的方法,其中物体(静止或运动)的图像被拍摄并分析以客观地获得目标质量。在这个拟议的计划中,CV技术将被开发,以表征加拿大谷物委员会定义的主要质量决定因素(损坏,健全程度,异物和其他脉冲类的混合)的前三名的脉冲(扁豆,干豌豆和干豆)在加拿大。将开发和测试用于单色相机、红绿蓝(RGB)彩色相机和近红外(NIR)相机的CV系统,该系统具有优化的照明、图像处理、特征提取、机器学习算法和分类模型。所开发的算法将被用来实现一个自动化的在线分级系统的脉冲处理设施的加拿大。这将有助于确保在国际市场上“加拿大脉搏保证”印章的有效性。此外,开发的协议将有益地补充其他正在进行的加拿大脉冲研究计划,如那些专注于存储(颜色退化)和育种(品种纯度的模式识别)。能力建设和知识传播:10名HQP(1名PDF,1名博士,3名硕士和5名UG)将接受食品安全和质量自动化无损检测程序的培训。在这一领域接受的培训将转移到涉及其他食品的类似研究或工业应用。将为加拿大豆类部门的农民、加工者和贸易商举办一次讲习班,以传播已开发的技术。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Manickavasagan, Annamalai其他文献

Quantitative detection of metanil yellow adulteration in chickpea flour using line-scan near-infrared hyperspectral imaging with partial least square regression and one-dimensional convolutional neural network
  • DOI:
    10.1016/j.jfca.2023.105290
  • 发表时间:
    2023-04-04
  • 期刊:
  • 影响因子:
    4.3
  • 作者:
    Saha, Dhritiman;Senthilkumar, T.;Manickavasagan, Annamalai
  • 通讯作者:
    Manickavasagan, Annamalai
Feasibility of storing canola at different moisture contents in silo bags under Canadian Prairie conditions
  • DOI:
    10.7451/cbe.2016.58.3.9
  • 发表时间:
    2016-01-01
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Chelladurai, Vellaichamy;Jian, Fuji;Manickavasagan, Annamalai
  • 通讯作者:
    Manickavasagan, Annamalai
Comparative assessment of blood glucose monitoring techniques: a review
  • DOI:
    10.1080/03091902.2022.2100496
  • 发表时间:
    2023-02-17
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Ahmadian, Nivad;Manickavasagan, Annamalai;Ali, Amanat
  • 通讯作者:
    Ali, Amanat

Manickavasagan, Annamalai的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Manickavasagan, Annamalai', 18)}}的其他基金

Development of thermal imaging system to assure safety and quality of ready to eat chicken products****
开发热成像系统以确保即食鸡肉产品的安全和质量****
  • 批准号:
    536482-2018
  • 财政年份:
    2018
  • 资助金额:
    $ 2.26万
  • 项目类别:
    Engage Grants Program

相似国自然基金

基于SOPC的VisionTransformer模型AI推理系统实现研究
  • 批准号:
    2023JJ60221
  • 批准年份:
    2023
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
老年人群视障风险VISION管控模式构建与实证研究
  • 批准号:
    71974198
  • 批准年份:
    2019
  • 资助金额:
    48.5 万元
  • 项目类别:
    面上项目

相似海外基金

Development of medical computer vision system and the clinical application
医学计算机视觉系统开发及临床应用
  • 批准号:
    23K07084
  • 财政年份:
    2023
  • 资助金额:
    $ 2.26万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
SCH: Computer Vision Algorithms to Detect Tics In Patients with Tourette Syndrome
SCH:用于检测抽动秽语综合征患者抽动的计算机视觉算法
  • 批准号:
    10817272
  • 财政年份:
    2023
  • 资助金额:
    $ 2.26万
  • 项目类别:
Computer Vision for Malaria Microscopy: Automated Detection and Classification of Plasmodium for Basic Science and Pre-Clinical Applications
用于疟疾显微镜的计算机视觉:用于基础科学和临床前应用的疟原虫自动检测和分类
  • 批准号:
    10576701
  • 财政年份:
    2023
  • 资助金额:
    $ 2.26万
  • 项目类别:
Motor neural dynamics of free behavior enabled through 3D computer vision
通过 3D 计算机视觉实现自由行为的运动神经动力学
  • 批准号:
    10546485
  • 财政年份:
    2022
  • 资助金额:
    $ 2.26万
  • 项目类别:
I-Corps: Computer Vision-Based Intelligent Service Recommendation System
I-Corps:基于计算机视觉的智能服务推荐系统
  • 批准号:
    2223872
  • 财政年份:
    2022
  • 资助金额:
    $ 2.26万
  • 项目类别:
    Standard Grant
Continuous ADL monitoring using computer vision to maintain independence and improve HRQoL in older adults at risk for AD/ADRD
使用计算机视觉进行连续 ADL 监测,以保持独立性并改善有 AD/ADRD 风险的老年人的 HRQoL
  • 批准号:
    10650307
  • 财政年份:
    2022
  • 资助金额:
    $ 2.26万
  • 项目类别:
Plastic packaging, a complete recognition and monitoring system based on AI and fusing RGB-based computer vision with Near Infrared spectral Imaging (NIR SI)
塑料包装,基于人工智能并将基于 RGB 的计算机视觉与近红外光谱成像 (NIR SI) 融合的完整识别和监控系统
  • 批准号:
    10020954
  • 财政年份:
    2022
  • 资助金额:
    $ 2.26万
  • 项目类别:
    Collaborative R&D
SBIR Phase I: A computer vision system for calorie tracking to encourage adherence to customized weight-loss regimens
SBIR 第一阶段:用于卡路里跟踪的计算机视觉系统,以鼓励遵守定制的减肥方案
  • 批准号:
    2136886
  • 财政年份:
    2022
  • 资助金额:
    $ 2.26万
  • 项目类别:
    Standard Grant
Computer vision system for characterization of Canadian pulses
用于表征加拿大豆类的计算机视觉系统
  • 批准号:
    RGPIN-2019-05140
  • 财政年份:
    2022
  • 资助金额:
    $ 2.26万
  • 项目类别:
    Discovery Grants Program - Individual
Motor neural dynamics of free behavior enabled through 3D computer vision
通过 3D 计算机视觉实现自由行为的运动神经动力学
  • 批准号:
    10367903
  • 财政年份:
    2022
  • 资助金额:
    $ 2.26万
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了