Which extraction technique is more appropriate for rice plant disease detection in digital image preprocessing?

22 June 2023 1 3K Report

I have a dataset of rice leaf for training and testing in machine learning. Here is the link: https://data.mendeley.com/datasets/znsxdctwtt/1

I want to develop my project with these techniques;

RGB Image Acquisition & Preprocessing (HSV Conversation, Thresholding and Masking)

Image Segmentation(GLCM matrices, Wavelets(DWT))

Classifications (SVM, CNN ,KNN, Random Forest)

Results with Matlab Codings.

But I have a confusion for final scores for confusion matrices. So I need any technique to check which extraction method is good for dataset.
My main target is detection normal and abnormal(disease) leaf with labels.

#image #processing #mathematics #machinelearning #matlab #deeplearning

Hlaing Htake Khaung Tin

There are two commonly used extraction techniques that can be appropriate for rice plant disease detection: (1) Color-based Extraction and (2) Texture-based Extraction.The most appropriate extraction technique for rice plant disease detection depends on the specific requirements and characteristics of the dataset and the detection algorithm being used.

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