Detection, Quantification and Analysis of Neofabraea Leaf Spot in Olive Plant using Image Processing Techniques

被引:0
|
作者
Sinha, Aditya [1 ]
Shekhawat, Rajveer Singh [1 ]
机构
[1] Manipal Univ Jaipur, Sch Comp & Informat Technol, Jaipur, Rajasthan, India
关键词
Image Processing; k-means; Olive; Plant disease; La*b*; Threshold; Leaf Spot; Neofabrea; SYMPTOMS; SEVERITY;
D O I
10.1109/ispcc48220.2019.8988316
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Plant diseases occur in various parts of plants and have a variety of identifying symptoms; the majority of them can be visually identified and evaluated. Barbedo [1] have thoroughly reviewed a variety of techniques used for detection, quantification and classification of plant diseases using image processing techniques. We have explored the plant diseases which are visually dominant and can be observed at the earlier stage of its life cycle. In this work, we have detected and quantified Neofabraea leaf spot in olive plants. The data has been collected from local olive farms and through online resources. We have isolated the Region of Interest(ROI) in the infected leaf using two different methodologies. Firstly we tried to apply thresholding technique on the Histogram values of the leaf image in the La*b* color model; we also have used the k-means based color segmentation on the RGB color model. Quantification of the disease is also performed using the ratio of the infected region by the whole area of the leaf and verified using visual identification.
引用
收藏
页码:348 / 353
页数:6
相关论文
共 50 条
  • [31] Debris flow detection using image processing techniques
    Chang, S. Y.
    Lin, C. P.
    DEBRIS-FLOW HAZARDS MITIGATION: MECHANICS, PREDICTION, AND ASSESSMENT, 2007, : 549 - +
  • [32] Breast cancer detection using image processing techniques
    Cahoon, TC
    Sutton, MA
    Bezdek, JC
    NINTH IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2000), VOLS 1 AND 2, 2000, : 973 - 976
  • [33] Detection and Counting of Pothole using Image Processing Techniques
    Vigneshwar, K.
    Kumar, Hema B.
    2016 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMPUTING RESEARCH, 2016, : 375 - 378
  • [34] Optic Disc Detection Using Image Processing Techniques
    Cetiner, Halit
    Cetisli, Bayram
    2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2014, : 1075 - 1078
  • [35] Hazard detection on runways using image processing techniques
    Rajput, Girish Singh
    Rahman, Zia-ur
    ENHANCED AND SYNTHETIC VISION 2008, 2008, 6957
  • [36] Detection of Counterfeit Currency using Image Processing Techniques
    Dhapare, Priyanka
    Agarwal, Akash
    Doshi, Devangi
    2019 IEEE 5TH INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT), 2019,
  • [37] Lane Departure Detection Using Image Processing Techniques
    Baili, Jamel
    Marzougui, Mehrez
    Sboui, Ameur
    Lahouar, Samer
    Hergli, Mounir
    Bose, J. Subash Chandra
    Besbes, Kamel
    2017 2ND INTERNATIONAL CONFERENCE ON ANTI-CYBER CRIMES (ICACC), 2017, : 238 - 241
  • [38] Breast Cancer Detection Using Image Processing Techniques
    Gupta, Siddhartha
    Sinha, Neha
    Sudha, R.
    Babu, Challa
    2019 INNOVATIONS IN POWER AND ADVANCED COMPUTING TECHNOLOGIES (I-PACT), 2019,
  • [39] Detection of Diseases in Sugarcane Using Image Processing Techniques
    Thilagavathi, K.
    Kavitha, K.
    Praba, R. Dhivya
    Arina, S. V. Arockia Joseph
    Sahana, R. C.
    BIOSCIENCE BIOTECHNOLOGY RESEARCH COMMUNICATIONS, 2020, 13 (11): : 109 - 115
  • [40] Detection of Glaucoma Using Image Processing Techniques: A Critique
    Kumar, B. Naveen
    Chauhan, R. P.
    Dahiya, Nidhi
    SEMINARS IN OPHTHALMOLOGY, 2018, 33 (02) : 275 - 283