Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics
Rukaiyya Pyarelal Shaikh
Unknown Affiliation
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Review of Leaf Unhealthy Region Detection Using Image Processing Techniques S. A. Dhole; Rukaiyya Pyarelal Shaikh
Bulletin of Electrical Engineering and Informatics Vol 5, No 4: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (176.287 KB) | DOI: 10.11591/eei.v5i4.498

Abstract

Abstract- In agricultural  field the plants comes to an attack from the various pets bacterial and micro-organism diseases. This diseases  attacks on the plant leaves, steams, and fruit part. This present review paper discussed the image processing techniques which is used in performing the early detection of plant diseases through leaf feature inspection. the basic objective of this work is to develop image analysis and classification techniques for extraction and finally classified the diseases present on leaf. Image of leaf is captured  and the process is performed and to determine the status of each plant. Here proposed model  divide into four parts. The  image preprocessing including normalization and contrast adjustment; segment the region of interest  determine by using color transform YCbCr and bi-level thresholding for statistical usage to determine the defect and severity area of plant leaves. The texture feature extraction using statistical GLCM (Gray Level Co-occurrences Matrix)  and color feature by means values.[1] Finally classification achieved using random markov model.
Review of Leaf Unhealthy Region Detection Using Image Processing Techniques S. A. Dhole; Rukaiyya Pyarelal Shaikh
Bulletin of Electrical Engineering and Informatics Vol 5, No 4: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (176.287 KB) | DOI: 10.11591/eei.v5i4.498

Abstract

Abstract- In agricultural  field the plants comes to an attack from the various pets bacterial and micro-organism diseases. This diseases  attacks on the plant leaves, steams, and fruit part. This present review paper discussed the image processing techniques which is used in performing the early detection of plant diseases through leaf feature inspection. the basic objective of this work is to develop image analysis and classification techniques for extraction and finally classified the diseases present on leaf. Image of leaf is captured  and the process is performed and to determine the status of each plant. Here proposed model  divide into four parts. The  image preprocessing including normalization and contrast adjustment; segment the region of interest  determine by using color transform YCbCr and bi-level thresholding for statistical usage to determine the defect and severity area of plant leaves. The texture feature extraction using statistical GLCM (Gray Level Co-occurrences Matrix)  and color feature by means values.[1] Finally classification achieved using random markov model.
Review of Leaf Unhealthy Region Detection Using Image Processing Techniques S. A. Dhole; Rukaiyya Pyarelal Shaikh
Bulletin of Electrical Engineering and Informatics Vol 5, No 4: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (176.287 KB) | DOI: 10.11591/eei.v5i4.498

Abstract

Abstract- In agricultural  field the plants comes to an attack from the various pets bacterial and micro-organism diseases. This diseases  attacks on the plant leaves, steams, and fruit part. This present review paper discussed the image processing techniques which is used in performing the early detection of plant diseases through leaf feature inspection. the basic objective of this work is to develop image analysis and classification techniques for extraction and finally classified the diseases present on leaf. Image of leaf is captured  and the process is performed and to determine the status of each plant. Here proposed model  divide into four parts. The  image preprocessing including normalization and contrast adjustment; segment the region of interest  determine by using color transform YCbCr and bi-level thresholding for statistical usage to determine the defect and severity area of plant leaves. The texture feature extraction using statistical GLCM (Gray Level Co-occurrences Matrix)  and color feature by means values.[1] Finally classification achieved using random markov model.
Co-Authors S. A. Dhole