We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
LEAF DISEASE RECOGNITION USING SEGMENTATION WITH VISUAL FEATURE DESCRIPTOR.
- Authors
Angayarkanni, D.; Jayasimman, L.
- Abstract
Agriculture has become the main sources of the income for many developed countries. The productivity in agriculture can be affected by various diseases present in the plant due to climatic conditions. The key step to improve the productivity of crops are to detect the disease at the preliminary stage. Automation becomes the best solution for this because it is more difficult to observe the disorders in plants parts. For that an image of affected plant leaf is acquired and segments the affected portion and to recognize the disease by using image processing and computer vision and machine learning techniques. The extracted features from the segmented portion are descripted using Global and Local Visual descriptors. Finally, we use the classifier to recognize the disease. Extracting a meaningful feature from an image is a central problem for a variety of computer vision problems like recognition, image retrieval, and classification. In this research, visual feature descriptor that best describe an image with respect to its visual property is explored. It is specifically focusing on recognizing tasks. The experimental results have proved that the combination of visual descriptors with various classifiers such as SVM and Ensemble Classifier produces high quality outcomes when compared to individual descriptors.
- Subjects
COMPUTER vision; IMAGE processing; PLANT diseases; IMAGE retrieval; DEVELOPED countries
- Publication
ICTACT Journal on Image & Video Processing, 2022, Vol 12, Issue 3, p2624
- ISSN
0976-9099
- Publication type
Article
- DOI
10.21917/ijivp.2022.0372