ICSPI: Intelligent Classification System of Pest Insects Based on Image Processing and Neural Arbitration

2017 ◽  
Vol 33 (4) ◽  
pp. 453-460 ◽  
Author(s):  
Kamil Dimililer ◽  
Salah Zarrouk
Keyword(s):  
Image Processing ◽  
Classification System ◽  
Intelligent Systems ◽  
High Efficiency ◽  
Backpropagation Neural Network ◽  
Classification Rate ◽  
Geometric Shapes ◽  
Image Processing Techniques ◽  
Significant Challenge ◽  
Processing Techniques

Abstract. Detection of insects in agricultural fields is a significant challenge. Minimizing the use of pesticides is necessary for healthier crops and consumers. Therefore, effective and intelligent systems should be designed to fight infestations. This article aims to develop an intelligent insect classification system that would be capable of detecting and classifying the eight insects most commonly found in paddy fields. The developed system comprises two principal stages. In the first stage, the images of the insects are processed using different image processing techniques in order to detect their geometric shapes. The next stage is the classification phase, where a backpropagation neural network is trained and then tested on processed images. Experimentally, the system was tested on different insect images and the results show high efficiency and a classification rate of 93.5%. Keywords: Backpropagation neural networks, Classification, Geometric shapes, Intelligent systems, Pattern averaging, Pest control.

scholarly journals Planning pesticides usage for herbal and animal pests based on intelligent classification system with image processing and neural networks

2018 ◽  
Vol 16 ◽  
pp. 01004
Author(s):  
Kamil Dimililer ◽  
Yoney Kirsal Ever
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Classification System ◽  
Intelligent Systems ◽  
Backpropagation Neural Network ◽  
Classification Rate ◽  
Geometric Patterns ◽  
Second Stage ◽  
Processing Techniques ◽  
Pesticide Usage

Pests are divided into two as herbal and animal pests in agriculture, and detection and use of minimum pesticides are quite challenging task. Last three decades, researchers have been improving their studies on these manners. Therefore, effective, efficient, and as well as intelligent systems are designed and modelled. In this paper, an intelligent classification system is designed for detecting pests as herbal or animal to use of proper pesticides accordingly. The designed system suggests two main stages. Firstly, images are processed using different image processing techniques that images have specific distinguishing geometric patterns. The second stage is neural network phase for classification. A backpropagation neural network is used for training and testing with processed images. System is tested, and experiment results show efficiency and effective classification rate. Autonomy and time efficiency within the pesticide usage are also discussed.

scholarly journals Image processing techniques for lemons and tomatoes classification

Bragantia ◽  
2008 ◽  
Vol 67 (3) ◽  
pp. 785-789 ◽  
Author(s):  
Antonio Carlos Loureiro Lino ◽  
Juliana Sanches ◽  
Inacio Maria Dal Fabbro
Keyword(s):  
Image Processing ◽  
Classification System ◽  
Fruit Shape ◽  
Morphological Operations ◽  
Border Detection ◽  
Image Processing Techniques ◽  
Operational Costs ◽  
Image Improvement ◽  
Processing Techniques ◽  
Vegetable Quality

Vegetable quality is frequently referred to size, shape, mass, firmness, color and bruises from which fruits can be classified and sorted. However, technological by small and middle producers implementation to assess this quality is unfeasible, due to high costs of software, equipment as well as operational costs. Based on these considerations, the proposal of this research is to evaluate a new open software that enables the classification system by recognizing fruit shape, volume, color and possibly bruises at a unique glance. The software named ImageJ, compatible with Windows, Linux and MAC/OS, is quite popular in medical research and practices, and offers algorithms to obtain the above mentioned parameters. The software allows calculation of volume, area, averages, border detection, image improvement and morphological operations in a variety of image archive formats as well as extensions by means of "plugins" written in Java.

scholarly journals Intelligent Systems to Predict and Diagnose Benign and Malignant Skin Lesions

2020 ◽  
Author(s):  
Geetha C ◽  
Aparna Darapaneni ◽  
Lakkamaneni Chandana Manaswini
Keyword(s):  
Image Processing ◽  
Health Informatics ◽  
Intelligent Systems ◽  
Skin Lesions ◽  
Improve Quality ◽  
Image Processing Techniques ◽  
Malignant Skin ◽  
Processing Software ◽  
Image Processing Software ◽  
Processing Techniques

The main purpose of Intelligent systems is to reason, calculate and perceive relationships and analogies. These Intelligent systems learn from experience and retrieve information from memory and provide the same to the users based onss their requirement. Currently, there is a trend for the use of intelligent systems in health informatics. The main objective of this is to improve quality, efficiency and availability of health services to people round the clock at a lower cost. Intelligent systems aim to predict and diagnose the skin cancer and abrasions based on their images. It understands the cause and thereby analyses the image based on some of the image processing techniques like patterns, anisotropic diffusion, image editing, independent component analysis and image restoration. We make use of image processing software which captures the image and then converts it to digital form and perform the required manipulations.

Three-Dimensional Structure of Rotavirus-Fab Complex

1990 ◽  
Vol 48 (1) ◽  
pp. 238-239
Author(s):  
B.V.V. Prasad ◽  
E. Marietta ◽  
J.W. Burns ◽  
M.K. Estes ◽  
W. Chiu
Keyword(s):  
Image Processing ◽  
Smooth Surface ◽  
Three Dimensional ◽  
Outer Shell ◽  
Dimensional Structure ◽  
Structural Studies ◽  
Cell Penetration ◽  
Electron Cryomicroscopy ◽  
Image Processing Techniques ◽  
Processing Techniques

Rotaviruses are spherical, double-shelled particles. They have been identified as a major cause of infantile gastroenteritis worldwide. In our earlier studies we determined the three-dimensional structures of double-and single-shelled simian rotavirus embedded in vitreous ice using electron cryomicroscopy and image processing techniques to a resolution of 40Å. A distinctive feature of the rotavirus structure is the presence of 132 large channels spanning across both the shells at all 5- and 6-coordinated positions of a T=13ℓ icosahedral lattice. The outer shell has 60 spikes emanating from its relatively smooth surface. The inner shell, in contrast, exhibits a bristly surface made of 260 morphological units at all local and strict 3-fold axes (Fig.l).The outer shell of rotavirus is made up of two proteins, VP4 and VP7. VP7, a glycoprotein and a neutralization antigen, is the major component. VP4 has been implicated in several important functions such as cell penetration, hemagglutination, neutralization and virulence. From our earlier studies we had proposed that the spikes correspond to VP4 and the rest of the surface is composed of VP7. Our recent structural studies, using the same techniques, with monoclonal antibodies specific to VP4 have established that surface spikes are made up of VP4.

A Survey on Detection and Classification of Brain Tumor Using Image Processing Techniques

2020 ◽  
pp. 967-973
Author(s):  
V. Deepika ◽  
T. Rajasenbagam
Keyword(s):  
Image Processing ◽  
Brain Tumor ◽  
Soft Tissues ◽  
Tumor Detection ◽  
Tumor Classification ◽  
Normal Brain ◽  
Image Processing Techniques ◽  
Normal Brain Function ◽  
Processing Techniques ◽  
The Brain

A brain tumor is an uncontrolled growth of abnormal brain tissue that can interfere with normal brain function. Although various methods have been developed for brain tumor classification, tumor detection and multiclass classification remain challenging due to the complex characteristics of the brain tumor. Brain tumor detection and classification are one of the most challenging and time-consuming tasks in the processing of medical images. MRI (Magnetic Resonance Imaging) is a visual imaging technique, which provides a information about the soft tissues of the human body, which helps identify the brain tumor. Proper diagnosis can prevent a patient's health to some extent. This paper presents a review of various detection and classification methods for brain tumor classification using image processing techniques.

Rice Panicle Blast Detection and Grading Based on Image Processing Techniques

2019 ◽  
Vol 7 (5) ◽  
pp. 165-168 ◽  
Author(s):  
Prabira Kumar Sethy ◽  
Swaraj Kumar Sahu ◽  
Nalini Kanta Barpanda ◽  
Amiya Kumar Rath
Keyword(s):  
Image Processing ◽  
Image Processing Techniques ◽  
Panicle Blast ◽  
Processing Techniques

Identification of Cucumber Leaf Disease using Image Processing Techniques

2018 ◽  
Vol 6 (6) ◽  
pp. 1493-1499
Author(s):  
Shrutika.C.Rampure . ◽  
Dr. Vindhya .P. Malagi ◽  
Dr. Ramesh Babu D.R
Keyword(s):  
Image Processing ◽  
Image Processing Techniques ◽  
Leaf Disease ◽  
Processing Techniques
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