scholarly journals Brain Cancer Detection using Neuro Fuzzy Logic

2011 ◽  
pp. 58-61
Author(s):  
Laxmi Ghodke ◽  
Apeksha Naik ◽  
Rahul Konale ◽  
Suchit Mehta
Keyword(s):  
Cancer Detection ◽  
Brain Cancer ◽  
Brain Mri ◽  
Fuzzy Approach ◽  
Image Processing Techniques ◽  
Neuro Fuzzy ◽  
Different Types ◽  
Processing Techniques ◽  
The Given ◽  
Aided Diagnosis

This paper presents an approach of computer-aided diagnosis for early prediction of cancer cells in brain. It extracts the texture from the given brain MRI sample.It uses image processing techniques followed by neuro classification for prediction of Cancer for a given MRI sample. A neuro fuzzy approach is used for the recognition of the extracted region. The implementation is observed on various types of MRI images with different types of cancer regions.

scholarly journals Classification Of Wheat Grains Using Image Processing Techniques Based Neuro-Fuzzy System Model

2018 ◽  
pp. 57-61
Author(s):  
Ahmet Kayabasi ◽  
Kadir Sabanci ◽  
Abdurrahim Toktas
Keyword(s):  
Image Processing ◽  
Fuzzy System ◽  
Absolute Error ◽  
Data Set ◽  
Wheat Grains ◽  
Image Processing Techniques ◽  
Neuro Fuzzy ◽  
Length Width ◽  
Processing Techniques

In this study, an image processing techniques (IPTs) and a Sugeno-typed neuro-fuzzy system (NFS) model is presented for classifying the wheat grains into bread and durum. Images of 200 wheat grains are taken by a high resolution camera in order to generate the data set for training and testing processes of the NFS model. The features of 5 dimensions which are length, width, area, perimeter and fullness are acquired through using IPT. Then NFS model input with the dimension parameters are trained through 180 wheat grain data and their accuracies are tested via 20 data. The proposed NFS model numerically calculate the outputs with mean absolute error (MAE) of 0.0312 and classify the grains with accuracy of 100% for the testing process. These results show that the IPT based NFS model can be successfully applied to classification of wheat grains.

Neuro-Fuzzy Approach Toward Segmentation of Brain MRI Based on Intensity and Spatial Distribution

2010 ◽  
Vol 41 (2) ◽  
pp. 66-71 ◽  
Author(s):  
Kaliyil Janardhan Shanthi ◽  
Madhavan Nair Sasikumar ◽  
Chandrasekharan Kesavadas
Keyword(s):  
Spatial Distribution ◽  
Brain Mri ◽  
Fuzzy Approach ◽  
Neuro Fuzzy

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 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.

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.

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