Rice Disease Detection Based on Image Processing Technique

2020 ◽  
pp. 135-145
Author(s):  
Md. Asfaqur Rahman ◽  
Md. Shahriar Nawal Shoumik ◽  
Md. Mahbubur Rahman ◽  
Most. Hasna Hena
Keyword(s):  
Image Processing ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Disease Detection ◽  
Rice Disease

Handheld Device Based on Image Processing Technique for Detecting Multiple Diseases of Apple Leaves

2019 ◽  
Vol 16 (10) ◽  
pp. 4160-4163 ◽  
Author(s):  
Swati Singh ◽  
Sheifali Gupta ◽  
Rupesh Gupta
Keyword(s):  
Image Processing ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Disease Detection ◽  
Normal Leaf ◽  
Handheld Device ◽  
Apple Leaves ◽  
Occurrence Matrix ◽  
Conventional Detection

The present invention discloses a handheld device for multiple disease detection from apple leaf and method thereof. An algorithm is developed in combination with image processing and gray level co occurrence matrix for the classification of normal leaf and diseased apple leaf. The device performs image processing by segmentation of the image and then by using extracted features. The classification and detection of these diseases impart an early solution to the farmers leading less harm to the apple crops. Conventional Detection of the diseases through naked eye can sometimes be faulty. Therefore the device of present invention helps farmers to detect the accurate diseases and provide timely solutions for the same. The present invention increases the throughput and reduces subjectiveness of the previously used conventional methods by proving early and precise disease detection from apple leaves.

scholarly journals Identification of Leaf Disease Using Image Processing Technique

2021 ◽  
pp. 881-885
Author(s):  
Ankit Wagh ◽  
Ritwik Chumble ◽  
Santosh Kangane ◽  
Pranav Bakare
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Plant Disease ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Disease Detection ◽  
Revolutionary Change ◽  
Leaf Disease ◽  
Important Time

The increased availability of smartphones has made it easier for taking technology to every individual. Technology can play important role in the field of agriculture to improve outcomes. Plant disease is one of the important reasons for the decrement of yield. Bridging technology with agriculture can give revolutionary change. It is challenging to monitor the disease of plants manually. It consumes important time, resources, and need efforts. Hence faster image processing technique is used as a solution for it. Disease detection using image processing involves multiple steps like the acquisition of images, pre-processing, segmentation, feature extraction, and classification. This paper discusses a faster image processing technique using the KNN method. This algorithm gives an asymptotically faster method for image processing.

A New Image Processing Technique for STEM

1974 ◽  
Vol 32 ◽  
pp. 432-433
Author(s):  
Yasushi Kokubo ◽  
Hirotami Koike ◽  
Teruo Someya
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Elastic Scattering ◽  
Field Emission ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Energy Analyzer ◽  
Scanning Microscope ◽  
Scanning Electron

One of the advantages of scanning electron microscopy is the capability for processing the image contrast, i.e., the image processing technique. Crewe et al were the first to apply this technique to a field emission scanning microscope and show images of individual atoms. They obtained a contrast which depended exclusively on the atomic numbers of specimen elements (Zcontrast), by displaying the images treated with the intensity ratio of elastically scattered to inelastically scattered electrons. The elastic scattering electrons were extracted by a solid detector and inelastic scattering electrons by an energy analyzer. We noted, however, that there is a possibility of the same contrast being obtained only by using an annular-type solid detector consisting of multiple concentric detector elements.

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

An Enhanced Technique for Classification of Fruits using Shape Color and Texture Features

2017 ◽  
Vol 7 (7) ◽  
pp. 408
Author(s):  
Yashpal Jitarwal ◽  
Tabrej Ahamad Khan ◽  
Pawan Mangal
Keyword(s):  
Image Processing ◽  
Texture Features ◽  
Automatic Classification ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Advance Technique ◽  
Time Required ◽  
Fruit Sorting ◽  
Human Inspection

In earlier times fruits were sorted manually and it was very time consuming and laborious task. Human sorted the fruits of the basis of shape, size and color. Time taken by human to sort the fruits is very large therefore to reduce the time and to increase the accuracy, an automatic classification of fruits comes into existence.To improve this human inspection and reduce time required for fruit sorting an advance technique is developed that accepts information about fruits from their images, and is called as Image Processing Technique.

Sign in / Sign up

Export Citation Format

Share Document