IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v11y2025i3id1493.html

Cotton Leaf Disease Detection Through Image Processing Technique

Author

Listed:
  • Thamballa Aruna
  • G.V.S. Ananthnath

Abstract

Agriculture is an important industry in many countries. As farm production is a large part of India's financial system, it is extremely important to carefully examine the issues of food production. The scientific and economic importance of nomenclature and recognition of plant infections are increasing, There is a need for a method or system that can automatically diagnose diseases because it can revolutionize surveillance. You can ingest huge harvest fields and plant leaves. Diagnosis of cotton disease is important to prevent catastrophic outbreaks. Immediately after the detection of disease, the purpose of this study is to issue guidelines for the creation of applications to detect wattage blade disease. To use this, the user must first submit a photo of the cotton blade and then use image processing to obtain a digitized color image of the damaged sheet. Get a digitized color image of this sheet. This can be handled using a mobile set algorithm to expect the true cause of wattage blade disease.

Suggested Citation

  • Thamballa Aruna & G.V.S. Ananthnath, 2025. "Cotton Leaf Disease Detection Through Image Processing Technique," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11(3), pages 593-601, June.
    • Handle: RePEc:jbh:ijsrcs:v11:y2025:i3:id:1493
    DOI: 10.32628/CSEIT25113320
    Note: Article URL: https://ijsrcseit.com/home/article/view/CSEIT25113320
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/home/article/view/CSEIT25113320
    File Function: Article URL
    Download Restriction: no
    File URL: https://ijsrcseit.com/home/article/download/CSEIT25113320/CSEIT25113320
    File Function: Full text
    Download Restriction: no
    File URL: https://libkey.io/10.32628/CSEIT25113320?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jbh:ijsrcs:v11:y2025:i3:id:1493. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pankaj Sharma (USA) (email available below). General contact details of provider: https://ijsrcseit.com/home .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.