Comparison of Features Extraction Algorithms Used in the Diagnosis of Plant Diseases

Abstract

The detection of diseases affecting plant is very important as it relates to the issue of food security, which is a very serious threat to human life. The system of diagnosis of diseases involves a series of steps starting with the acquisition of images through the pre-processing, segmentation and then features extraction that is our subject finally the process of classification. Features extraction is a very important process in any diagnostic system where we can compare this stage to the spine in this type of system. It is known that the reason behind this great importance of this stage is that the process of extracting features greatly affects the work and accuracy of classification. Proper selection of the right features leads to high accuracy in the system diagnostics and vice versa. The proposed system collect images of different crop (Rice, cotton and tomato) disease, we will enter the images of cropping them , then Re-size the images to fixed size, then improve the image through Fuzzy histogram equalization (FHE) , then perform image segmentation using color based K-means and finally compare the methods of features extraction (Percentage of Leaf Area Infected (PI),Texture-Based Features, Color Moments, Features obtained by Color Co-occurrence Method and Shape based Features) we found that the use of 4 methods together (Percentage of Leaf Area Infected (PI),Texture-Based Features, Color Moments and Shape based Features) produce excellent result..

A study for the changes of lipid profile in sera of patients infected with viral hepatitis type B and C infections

“…Liver function parameters significantly increased in both HCV and HBV patients. Therefore, these parameters were used to assess parameters of interest for comparison between both HBV and HCV patients and control group as used by other researches ( 19,20). Interactions between chronic hepatitis C virus (HCV) infection and lipid metabolism have been described in some studies (8,9,21,22).…”

Effect of Stimulate of Sorghum Seeds with Banana Peel Extract and Citric Acid on Seeds Viability and Vigour

“…Seeds can be stimulated by plant extracts as they contain natural compounds that encourage germination and growth [00] in addition to being cheap, easy to use and environmentally friendly. Plant extract have a positive role in increasing the germination ratio [12]. Banana peels contain a high ratio of nutrients that encourage growth, especially nitrogen and potassium [13].…”

Studying the Classification of Texture Images by K-Means of Co-Occurrence Matrix and Confusion Matrix

“…One of the most important statistical methods is the gray-level presence matrix (GLCM), considered one of the oldest methods for extracting many texture features [21]. The co-occurrence matrix Co (i, j) calculates these features.…”

“…The co-occurrence matrix Co (i, j) calculates these features. It finds the gray levels i and j, respectively, with the number of pixel co-occurrence, within a certain distance [21][22][23]. The result of this is a matrix of distance d and direction for every number of intensity levels observed in the image.…”

“…After creating (GLCM), the statistical characteristics are calculated as an example. Six statistical properties can be inferred from (GLCM) (Contrast, correlation, energy, homogeneity, Entropy, and maximum probability [21]. This research is to study the features of texture images taken from the Brodatz database for different angles and its impact on the classification results in terms of the distribution of images in various classes and the percentage of agreement between them on the classification of images.…”