scholarly journals OBSESSION AND ADVERSE EFFECTS OVER TECHNOLOGY

2017 ◽  
Vol 5 (6) ◽  
pp. 247-254
Author(s):  
Mary Ivy Deepa ◽  
Mithra ◽  
Savithri
Keyword(s):  
Image Processing ◽  
Adverse Effects ◽  
Statistical Study ◽  
Electronic Devices ◽  
Image Processing Techniques ◽  
Normal Life ◽  
Different Types ◽  
Negative Impacts ◽  
Processing Techniques

An increase in the usage of electronic devices in today’s world leads to a negative impacts on humans. Due to the over-usage of the devices leads to an uncontrollable handling behavior towards them called obsession. This paper deals with the statistical study about the obsession among the group of students and applying image processing techniques for recognition or detection of different types diseases/ symptoms caused by the obsession and explaining the consequences meeting with the obsession of the electronic devices among students normal life.

AIRCRAFT CLASSIFICATION USING IMAGE PROCESSING TECHNIQUES AND ARTIFICIAL NEURAL NETWORKS

2011 ◽  
Vol 25 (08) ◽  
pp. 1321-1335 ◽  
Author(s):  
ADIL GURSEL KARACOR ◽  
ERDAL TORUN ◽  
RASIT ABAY
Keyword(s):  
Image Processing ◽  
Image Data ◽  
Radar Data ◽  
Still Image ◽  
Image Processing Techniques ◽  
Black And White ◽  
Rf Signals ◽  
Different Types ◽  
Artificial Neural ◽  
Processing Techniques

Identifying the type of an approaching aircraft, should it be a helicopter, a fighter jet or a passenger plane, is an important task in both military and civilian practices. The task in question is normally done by using radar or RF signals. In this study, we suggest an alternative method that introduces the use of a still image instead of RF or radar data. The image was transformed to a binary black and white image, using a Matlab script which utilizes Image Processing Toolbox commands of Matlab, in order to extract the necessary features. The extracted image data of four different types of aircraft was fed into a three-layered feed forward artificial neural network for classification. Satisfactory results were achieved as the rate of successful classification turned out to be 97% on average.

scholarly journals A Review On Leaves Disease Segmentation And Classification Techniques

2019 ◽  
pp. 132-140
Author(s):  
Soumya Ranjan Sahu ◽  
Chandra Sekhar Panda
Keyword(s):  
Image Processing ◽  
Human Health ◽  
Traditional Method ◽  
Plant Diseases ◽  
Image Processing Techniques ◽  
Naked Eye ◽  
The People ◽  
Different Types ◽  
Processing Techniques

Agriculture plays a major role in our society. Most of the people depend on agriculture for their living. It becomes very important part of society for their livelihood. But there are some problems on agriculture that directly or indirectly affect the human health and also economy. The major problem for agriculture is the plant diseases. This paper is based on a survey of different types of techniques used for segmenting and classification of plant diseases by using image processing techniques. By these techniques, we can easily detect the area of the infected part or can identify the type of disease. This paper gives various techniques used by various authors to detect the disease fast an accurately. They used different types of segmentation techniques like region based, clustering, thresolding etc. to detect the infected part of the leaves and by using the classifier they classify the disease name. The traditional method of naked eye observation can be overcome by introducing these methods. Main focus of our work is to analysis of fast and accurate techniques to identify the plant diseases.

scholarly journals An Overview of Image Processing Techniques for Detecting COVID-19 and Other Infectious Diseases

2021 ◽  
Vol 20 (1) ◽  
pp. 77-86
Author(s):  
Raiyan Islam ◽  
Shihab Uddin ◽  
Jamil Mahmud Sakib ◽  
Md. Shariful Islam ◽  
Tanvir Ahmed
Keyword(s):  
Image Processing ◽  
Infectious Diseases ◽  
Human Body ◽  
Medical Science ◽  
Processing System ◽  
Image Processing System ◽  
Image Processing Techniques ◽  
Different Types ◽  
Human Figure ◽  
Processing Techniques

Modern-day medical activities and disease recognition systems are mostly based on the usage of modern technologies. Image processing system is one of the most usable and highly valuable technologies which is used in numerous amount of disease detection process. In this paper, a review will be given based on detecting several infectious and cancerous diseases of different organs in a human body through applying different types of image processing techniques. Image processing system consists of several numbers of image processing techniques which apply to a different category of data and resources. The infectious diseases in a human body possess a certain amount of area in any organ of a human body. Modern medical science of these days is very much advanced that x-ray images, CT or MRI scan images can provide a digital image of a human figure and with the help of these images infections can easily be detected by applying image processing techniques to make sure certain region is affected. A detailed overview will be provided in this review that are the most used image processing techniques to get accurate results on detecting different types of infectious diseases. 

scholarly journals Pepper Powder Quality Identification System Based on Silent Angle Imagery

2020 ◽  
Vol 2 (1) ◽  
pp. 24
Author(s):  
Muhaimin Gusrin ◽  
Abdul Fadlil
Keyword(s):  
Image Processing ◽  
Research Method ◽  
Identification System ◽  
Original Image ◽  
Image Processing Techniques ◽  
Different Types ◽  
Angle Method ◽  
Pepper Powder ◽  
Processing Techniques

This research identifies the quality of pepper powder using a computer automatically. The research method uses the stationary angle method. The design of this system is done by image processing techniques. The image of ground pepper that has been taken is then cropped to remove the unused portion of the image. The next step is to convert the original image into grayscale and then convert it to binary. The parameter of the stationary angle is when it has an angle of less than or equal to 38 °, the ground pepper includes fine ground pepper. If the angle ranges from 38o to 40o, including medium powdered pepper, and if the angle is greater than 41o, including the texture of coarse pepper powder. Testing 3 different types of samples obtained 40 mesh is 35.18 o; for 20 mesh is 40.46o and 10 mesh is 41.66o. Therefore, it can be seen that the smaller the texture of the size of ground pepper, the finer the quality.Penelitian ini mengidentifikasi kualitas lada bubuk menggunakan komputer secara otomatis. Metode penelitian menggunakan metode sudut diam. Perancangan sistem ini dilakukan dengan teknik pengolahan citra. Citra lada bubuk yang telah diambil selanjutnya di-cropping untuk menghilangkan bagian citra yang tidak terpakai. Langkah selanjutnya adalah citra hasil asli tersebut dikonversi dalam bentuk grayscale dan selanjutnya dikonversi dalam bentuk biner. Parameter sudut diam adalah ketika memiliki sudut kurang dari atau sama dengan 38o, lada bubuk tersebut termasuk lada bubuk yang halus. Jika sudutnya berkisar antara 38o sampai 40o maka termasuk lada bubuk sedang, dan jika sudutnya lebih besar dari 41o maka termasuk tekstur lada bubuk kasar. Pengujian 3 jenis sampel yang berbeda didapatkan 40 mesh adalah 35,18o; untuk 20 mesh adalah 40,46o dan 10 mesh adalah 41,66o. Oleh karena itu dapat diketahui bahwa semakin kecil tekstur ukuran lada bubuk, semakin halus kualitasnya.

scholarly journals Diabetic Retinopathy Detection using Image Processing (GUI)

2019 ◽  
Vol 8 (2S3) ◽  
pp. 538-542
Keyword(s):  
Image Processing ◽  
Diabetic Retinopathy ◽  
User Interface ◽  
Adverse Effects ◽  
Graphical User Interface ◽  
Retinal Image ◽  
Processing Time ◽  
Image Processing Techniques ◽  
Major Disease ◽  
Processing Techniques

Diabetic Retinopathy is a major disease that has affected over 290 million people globally and 69.2 million people in India, the rate of people getting affected will increase exponentially in the coming years. Diabetic Retinopathy is an ailment linked to the fundus of the eye and can have adverse effects on the patient, if at all left undiagnosed respectively. Our project aims to construct a graphical user interface that can integrate image processing techniques together in order to predict whether the input fundus/retinal image received from the patient is affected with Diabetic Retinopathy or not; if affected, the graphical user interface will display the severity along with the required action needed to be undertaken by the user / patient. This essentially reduces the processing time involved in the process of detecting the disease and also the ophthalmologists can also have our graphical user interface as a backup that can be used for validating or assist in detecting the disease

scholarly journals Automatic Fish Cutting and Cleaning Machine using Digital Image Processing

2019 ◽  
Vol 8 (2) ◽  
pp. 612-615
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Rural Women ◽  
Living Standard ◽  
Image Processing Techniques ◽  
Different Types ◽  
Cleaning Machine ◽  
Processing Techniques ◽  
Day By Day

There are many varieties of fishes available in the market and the consumers are increasing day by day. This paper is mainly concentrated on automatic cleaning and cutting of fish. There is huge demand for fish cutting and cleaning machine in the market for easy use. Time and labor can be effectively managed if this type of machine is implemented in the fish market. This paper introduces the concept of Digital image processing technology to identify the various types of fishes and their sizes. Special convey rollers mechanism need to be designed and developed for handling different types of fishes. Technology will ensuring hygiene, quality and waste disposal. The following are the objectives of this paper design and implement Automatic Fish Cutting and Cleaning Machine. The shape, size of fish is analyzed using Digital Image Processing techniques. This will improve the living standard of rural women who sells different variety of fishes in the market, which empowers women in the society.

scholarly journals Implementing Various Noise Reduction Filters on Infected Coconut Images

2019 ◽  
Vol 8 (12) ◽  
pp. 3675-3678
Keyword(s):  
Climate Change ◽  
Image Processing ◽  
Noise Reduction ◽  
Crop Yield ◽  
Agricultural Crop ◽  
Image Processing Techniques ◽  
Crop Diseases ◽  
Different Types ◽  
Effective Diagnosis ◽  
Processing Techniques

In recent times, more people are returning to farming. The inexperienced farmers facing problems in getting high crop yield. One of the challenges is to control crop diseases and pests. The farmers are not aware of the Climate change-induced agricultural diseases and pests. The image processing techniques have an important part in recognizing the diseases and pests infestations in the agricultural crop. The image must be free of noise for effective diagnosis. This paper analyses the performance of various noises and different de-noising techniques on an infected coconut image. In this paper, a suitable de-noising technique to remove various kinds of noise in an image. The performance of the filters is compared for different types of noises and the quality is measured based on PSNR and MSE.

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.

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