Author: haroonkhan

Using different digital devices like digital cameras, mobile phones and laptop, we can capture the image of the leaf. Generally, image can be greyscale or color. Six images are considered standard as per the dataset. Out of six, three are colored and three are greyscale images. Our first task is to check whether the image…

In advanced machine learning, the classification is done by SVM. The SVMs aim to create a decision boundary using which we can identify boundary from two suitable output values. SVM is also used for classification purpose. It is a supervised algorithm with which we can the change the boundary position also. The points closer to…

We did image classification using classifiers. Based on the degree of disease in a leaf, a classifier is used for classification and classification depends on the features of the last step. In machine learning it is used to divide values into two groups: one of positive values and other of negative values, depending upon certain…

Using the methods as indicated earlier, the image is characterized and segmentation detects the diseased area of the leaf. By using below formula, we can calculate percentage of the infected area of the leaf. In the formula, DA is the diseased portion of the leaf area and LA is the total leaf area (Figure 6.6): IA=DALA×100.

The size reduction of the image data is done by feature extraction. The segmented region is very easy for doing study as it is filled with suitable colors and shapes. Most of the features are used to illustrate an image of paddy leaf.

K-​​​means cluster process is applied to the image to do cluster analysis. It is the best method to solve problems related to clustering of the best learning algorithms that solve the clustering problems. K-​​​means algorithm is used to detect the iterative K-​​​centers. The sum of distances of the data points is optimized from their centers.…

In this process, the image is divided into smaller parts called segments to make the analysis and further processing easy. An image is subdivided using segmentation. The segmentation of the image divides it into objects or regions. The subdivision of the image depends on the depth of the problem. Segmentation algorithms work basically on two…

Color image processing is very important for use of large digital images over websites. This includes image processing and color modeling by digital processing. In this method, HSI color processing is applied to the image to get enhanced image (see Figure 6.4). Based on the color perception, the color model device is chosen as HSI. In…

In this method, digital images are modified such that they become more acceptable images from the previous ones. With the help of image enhancement more study can be done on the obtained images, for example, detecting noise in the image, improving the brightness of the image and extracting required area from the image.

Image acquisition is obtained from a camera. It is the primary process in digital image processing. Basically, it involves various techniques like scaling, eliminating noise and enhancing the contrast of the image. The subjected leaf images are captured from highest resolution cameras with more pixel values such that obtained image can be processed with various…