Review



otsu algorithm for image thresholding  (MathWorks Inc)


Bioz Verified Symbol MathWorks Inc is a verified supplier  
  • Logo
  • About
  • News
  • Press Release
  • Team
  • Advisors
  • Partners
  • Contact
  • Bioz Stars
  • Bioz vStars
    • 90
      Buy from Supplier

    Structured Review

    MathWorks Inc otsu algorithm for image thresholding
    Artificial Neural Network (ANN) applications in hyperspectral image analysis of food products.
    Otsu Algorithm For Image Thresholding, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/otsu+algorithm+for+image+thresholding/pmc07890297-5-16-38
    Average 90 stars, based on 1 article reviews
    otsu algorithm for image thresholding - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review"

    Article Title: Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review

    Journal: Current Research in Food Science

    doi: 10.1016/j.crfs.2021.01.002

    Artificial Neural Network (ANN) applications in hyperspectral image analysis of food products.
    Figure Legend Snippet: Artificial Neural Network (ANN) applications in hyperspectral image analysis of food products.

    Techniques Used: Biomarker Discovery, Software

    Deep Learning (DL) applications in hyperspectral image analysis of food products.
    Figure Legend Snippet: Deep Learning (DL) applications in hyperspectral image analysis of food products.

    Techniques Used: Biomarker Discovery, Software, Activation Assay, Control, Extraction

    Support Vector Machines (SVM) applications in hyperspectral image analysis of food products.
    Figure Legend Snippet: Support Vector Machines (SVM) applications in hyperspectral image analysis of food products.

    Techniques Used: Plasmid Preparation, Biomarker Discovery, Software, Infection, Sampling

    Decision trees (DT) applications in hyperspectral image analysis of food products.
    Figure Legend Snippet: Decision trees (DT) applications in hyperspectral image analysis of food products.

    Techniques Used: Biomarker Discovery, Software, Selection, Infection

    Random Forest (RF) applications in hyperspectral image analysis of food products.
    Figure Legend Snippet: Random Forest (RF) applications in hyperspectral image analysis of food products.

    Techniques Used: Biomarker Discovery, Software, Virus, Infection

    k-Nearest Neighbor (k-NN) applications in hyperspectral image analysis of food products.
    Figure Legend Snippet: k-Nearest Neighbor (k-NN) applications in hyperspectral image analysis of food products.

    Techniques Used: Biomarker Discovery, Software, Residue, Extraction

    Related Articles

    Virus:

    Article Title: Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review
    Article Snippet: Identification of freezer burn on frozen salmon surface , 900–1700 , Standard normal variate (SNV) , Image thresholding , 50 , 75:25 , MATLAB R2015b , 98% , . .. Detection and classification of virus on tobacco leaves , 400–1000 , Standard normal variate (SNV); Successive projections algorithm (SPA) , Image thresholding , 71 , 67:33 , MATLAB , 85% , . .. Discrimination of kiwifruits treated with different concentrations of forchlorfenuron , 900–1700 , Standard normal variate (SNV); Successive projections algorithm (SPA) , Image thresholding , 200 , 67:33 , MATLAB R2012a , 94% , .

    other:

    Article Title: Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review
    Article Snippet: Detection of stored insects in rice and maize , 400–1000 , Normalization , Otsu algorithm for image thresholding , Back Propagation Neural Network , 01 , – , 03 , – , 01 , – , 60:40 , MATLAB R2009b , 98% , .

    Article Title: Fabrication of model ultrafiltration membranes with uniform, high aspect ratio pores
    Article Snippet: In this manuscript, we report the facile fabrication of large-area model membranes with highly uniform and high aspect ratio pores with diameters <20 nm.. These membranes are useful for fundamental investigations of separation by size exclusion in the ultrafiltration regime, where species to be separated from solution have dimensions of 1–100 nm.. Such investigations require membranes with narrow pores and high aspect ratios such that the Hagen–Poiseuille equation is followed, enabling well-known models such as the hindered transport model to be evaluated and other affecting factors to be ignored.

    Article Title: Cryogenic mechanical alloying of aluminum matrix composites for powder bed fusion additive manufacturing
    Article Snippet: Cryogenic mechanical alloying (cryomilling) was employed to fabricate aluminum matrix composite powder feedstock for additive manufacturing.. The high energy milling of the powder system induces a homogenous distribution of reinforcement particles in the matrix powder by recurrent fracture and cold welding.. In this study, aluminum matrix composite feedstock were produced via different cryomilling techniques at varying compositions, powder charges, and milling times.

    Article Title: Characterization of Silicon Nanowires Reflectance by Effective Index Due to Air-Silicon Ratio
    Article Snippet: Silicon Nanowires (SiNWs) enhance light collection efficiency which is key in the performance of many optical and optoelectronic devices.. We fabricated SiNWs by metal assisted chemical etching (MACE) and determined Air:Si ratios by analyzing SEM images of substrate surface by image thresholding technique in MATLAB.. For normal incidence, a minimum reflectance of around 0.2% was achieved for about 2μm long SiNW with a slight increase when etching time was increased from 30 minutes to 45 minutes.



    Similar Products

    two-dimensional otsu multi-threshold image segmentation based on hybrid whale optimization algorithm  (Multimed Inc)
    90
    Multimed Inc two-dimensional otsu multi-threshold image segmentation based on hybrid whale optimization algorithm
    Two Dimensional Otsu Multi Threshold Image Segmentation Based On Hybrid Whale Optimization Algorithm, supplied by Multimed Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/otsu+algorithm+for+image+thresholding/two+dimensional+otsu+multi+threshold+image+segmentation+based+on+hybrid+whale+optimization+algorithm/pm37361197-610-1-14
    Average 90 stars, based on 1 article reviews
    two-dimensional otsu multi-threshold image segmentation based on hybrid whale optimization algorithm - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    image processing algorithm based on the otsu’s thresholding method  (MathWorks Inc)
    90
    MathWorks Inc image processing algorithm based on the otsu’s thresholding method
    Image Processing Algorithm Based On The Otsu’s Thresholding Method, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/otsu+algorithm+for+image+thresholding/10__1088_slash_1757___899x_slash_1246_slash_1_slash_012015-75-16-23
    Average 90 stars, based on 1 article reviews
    image processing algorithm based on the otsu’s thresholding method - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier
    otsu algorithm for image thresholding  (MathWorks Inc)
    90
    MathWorks Inc otsu algorithm for image thresholding
    Artificial Neural Network (ANN) applications in hyperspectral image analysis of food products.
    Otsu Algorithm For Image Thresholding, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/otsu+algorithm+for+image+thresholding/pmc07890297-5-16-38
    Average 90 stars, based on 1 article reviews
    otsu algorithm for image thresholding - by Bioz Stars, 2026-09
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Artificial Neural Network (ANN) applications in hyperspectral image analysis of food products.

    Journal: Current Research in Food Science

    Article Title: Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review

    doi: 10.1016/j.crfs.2021.01.002

    Figure Lengend Snippet: Artificial Neural Network (ANN) applications in hyperspectral image analysis of food products.

    Article Snippet: Detection of stored insects in rice and maize , 400–1000 , Normalization , Otsu algorithm for image thresholding , Back Propagation Neural Network , 01 , – , 03 , – , 01 , – , 60:40 , MATLAB R2009b , 98% , .

    Techniques: Biomarker Discovery, Software

    Deep Learning (DL) applications in hyperspectral image analysis of food products.

    Journal: Current Research in Food Science

    Article Title: Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review

    doi: 10.1016/j.crfs.2021.01.002

    Figure Lengend Snippet: Deep Learning (DL) applications in hyperspectral image analysis of food products.

    Article Snippet: Detection of stored insects in rice and maize , 400–1000 , Normalization , Otsu algorithm for image thresholding , Back Propagation Neural Network , 01 , – , 03 , – , 01 , – , 60:40 , MATLAB R2009b , 98% , .

    Techniques: Biomarker Discovery, Software, Activation Assay, Control, Extraction

    Support Vector Machines (SVM) applications in hyperspectral image analysis of food products.

    Journal: Current Research in Food Science

    Article Title: Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review

    doi: 10.1016/j.crfs.2021.01.002

    Figure Lengend Snippet: Support Vector Machines (SVM) applications in hyperspectral image analysis of food products.

    Article Snippet: Detection of stored insects in rice and maize , 400–1000 , Normalization , Otsu algorithm for image thresholding , Back Propagation Neural Network , 01 , – , 03 , – , 01 , – , 60:40 , MATLAB R2009b , 98% , .

    Techniques: Plasmid Preparation, Biomarker Discovery, Software, Infection, Sampling

    Decision trees (DT) applications in hyperspectral image analysis of food products.

    Journal: Current Research in Food Science

    Article Title: Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review

    doi: 10.1016/j.crfs.2021.01.002

    Figure Lengend Snippet: Decision trees (DT) applications in hyperspectral image analysis of food products.

    Article Snippet: Detection of stored insects in rice and maize , 400–1000 , Normalization , Otsu algorithm for image thresholding , Back Propagation Neural Network , 01 , – , 03 , – , 01 , – , 60:40 , MATLAB R2009b , 98% , .

    Techniques: Biomarker Discovery, Software, Selection, Infection

    Random Forest (RF) applications in hyperspectral image analysis of food products.

    Journal: Current Research in Food Science

    Article Title: Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review

    doi: 10.1016/j.crfs.2021.01.002

    Figure Lengend Snippet: Random Forest (RF) applications in hyperspectral image analysis of food products.

    Article Snippet: Detection of stored insects in rice and maize , 400–1000 , Normalization , Otsu algorithm for image thresholding , Back Propagation Neural Network , 01 , – , 03 , – , 01 , – , 60:40 , MATLAB R2009b , 98% , .

    Techniques: Biomarker Discovery, Software, Virus, Infection

    k-Nearest Neighbor (k-NN) applications in hyperspectral image analysis of food products.

    Journal: Current Research in Food Science

    Article Title: Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review

    doi: 10.1016/j.crfs.2021.01.002

    Figure Lengend Snippet: k-Nearest Neighbor (k-NN) applications in hyperspectral image analysis of food products.

    Article Snippet: Detection of stored insects in rice and maize , 400–1000 , Normalization , Otsu algorithm for image thresholding , Back Propagation Neural Network , 01 , – , 03 , – , 01 , – , 60:40 , MATLAB R2009b , 98% , .

    Techniques: Biomarker Discovery, Software, Residue, Extraction