Retina images are obtained from the fundus camera a
nd graded by skilled professionals. However there i
s
considerable shortage of expert observers has encou
raged computer assisted monitoring. Evaluation of
blood vessels network plays an important task in a
variety of medical diagnosis. Manifestations of
numerous vascular disorders, such as diabetic retin
opathy, depend on detection of the blood vessels
network. In this work the fundus RGB image is used
for obtaining the traces of blood vessels and areas
of
blood vessels are used for detection of Diabetic Re
tinopathy (DR). The algorithm developed uses
morphological operation to extract blood vessels. M
ainly two steps are used: firstly enhancement opera
tion
is applied to original retina image to remove noise
and increase contrast of retinal blood vessels. Se
condly
morphology operations are used to take out blood ve
ssels. Experiments are conducted on publicly availa
ble
DIARETDB1 database. Experimental results obtained b
y using gray-scale images have been presented.
Performance analysis of retinal image blood vessel segmentationacijjournal
The retinal image diagnosis
is an important methodology for diabetic retinopathy detection and analysis. in
this paper, the morphological operations and svm classifier are used to detect and segment the blood
vessels from the retinal image. the proposed system consists of three stage
s
-
first is preprocessing of retinal
image to separate the green channel and second stage is retinal image enhancement and third stage is
blood vessel segmentation using morphological operations and svm classifier. the performance of the
proposed system is
analyzed using publicly available dataset
An Approach for the Detection of Vascular Abnormalities in Diabetic Retinopathyijdmtaiir
Diabetic Retinopathy is a common complication of
diabetes that is caused by changes in the blood vessels of the
retina. The blood vessels in the retina get altered. Exudates are
secreted, micro-aneurysms and hemorrhages occur in the
retina. The appearance of these features represents the degree
of severity of the disease. In this paper the proposed approach
detects the presence of abnormalities in the retina using image
processing techniques by applying morphological processing
techniques to the fundus images to extract features such as
blood vessels, micro aneurysms and exudates. These features
are used for the detection of severity of Diabetic Retinopathy.
It can quickly process a large number of fundus images
obtained from mass screening to help reduce the cost, increase
productivity and efficiency for ophthalmologists.
The legal cause of blindness for the workingage
population in western countries is Diabetic Retinopathy - a
complication of diabetes mellitus - is a severe and wide- spread
eye disease. Digital color fundus images are becoming
increasingly important for the diagnosis of Diabetic Retinopathy.
In order to facilitate and improve diagnosis in different ways, this
fact opens the possibility of applying image processing techniques
.Microaneurysms is the earliest sign of DR, therefore an
algorithm able to automatically detect the microaneurysms in
fundus image captured. Since microaneurysms is a necessary
preprocessing step for a correct diagnosis. Some methods that
address this problem can be found in the literature but they have
some drawbacks like accuracy or speed. The aim of this thesis is
to develop and test a new method for detecting the
microaneurysms in retina images. To do so preprocessing, gray
level 2D feature based vessel extraction is done using neural
network by using extra neurons which is evaluated on DRIVE
database which is superior than rulebased methods. To identify
microaneurysms in an image morphological opening and image
enhancement is performed. The complete algorithm is developed
by using a MATLAB implementation and the diagnosis in an
image can be estimated with the better accuracy and in shorter
time than previous techniques
An Automated Systems for the Detection of Macular Ischemia based-Diabetic Ret...iosrjce
The proposed methodology in this paper marks out application for automatic detection of eye
diseases called Macular Ischemia using image processing techniques. In semi urban and rural areas large
percentages of people suffer from various eye diseases. For diagnoses of various eye diseases, Image processing
technique is used. . Diseases occur in Macula from retinal images have a huge type of textures, shapes and at
times they are difficult to be recognised and identified by doctors. Thus we are trying to optimize and develop
such system which is based on smart image recognition/classification algorithms. This proposed system
provides accuracy, uniformity and speed in performance and a high credence coefficient in results interpreting.
Keywords: Macular Ischemia, diagnosis, textures, consistence
Segmentation of the Blood Vessel and Optic Disc in Retinal Images Using EM Al...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Performance analysis of retinal image blood vessel segmentationacijjournal
The retinal image diagnosis
is an important methodology for diabetic retinopathy detection and analysis. in
this paper, the morphological operations and svm classifier are used to detect and segment the blood
vessels from the retinal image. the proposed system consists of three stage
s
-
first is preprocessing of retinal
image to separate the green channel and second stage is retinal image enhancement and third stage is
blood vessel segmentation using morphological operations and svm classifier. the performance of the
proposed system is
analyzed using publicly available dataset
An Approach for the Detection of Vascular Abnormalities in Diabetic Retinopathyijdmtaiir
Diabetic Retinopathy is a common complication of
diabetes that is caused by changes in the blood vessels of the
retina. The blood vessels in the retina get altered. Exudates are
secreted, micro-aneurysms and hemorrhages occur in the
retina. The appearance of these features represents the degree
of severity of the disease. In this paper the proposed approach
detects the presence of abnormalities in the retina using image
processing techniques by applying morphological processing
techniques to the fundus images to extract features such as
blood vessels, micro aneurysms and exudates. These features
are used for the detection of severity of Diabetic Retinopathy.
It can quickly process a large number of fundus images
obtained from mass screening to help reduce the cost, increase
productivity and efficiency for ophthalmologists.
The legal cause of blindness for the workingage
population in western countries is Diabetic Retinopathy - a
complication of diabetes mellitus - is a severe and wide- spread
eye disease. Digital color fundus images are becoming
increasingly important for the diagnosis of Diabetic Retinopathy.
In order to facilitate and improve diagnosis in different ways, this
fact opens the possibility of applying image processing techniques
.Microaneurysms is the earliest sign of DR, therefore an
algorithm able to automatically detect the microaneurysms in
fundus image captured. Since microaneurysms is a necessary
preprocessing step for a correct diagnosis. Some methods that
address this problem can be found in the literature but they have
some drawbacks like accuracy or speed. The aim of this thesis is
to develop and test a new method for detecting the
microaneurysms in retina images. To do so preprocessing, gray
level 2D feature based vessel extraction is done using neural
network by using extra neurons which is evaluated on DRIVE
database which is superior than rulebased methods. To identify
microaneurysms in an image morphological opening and image
enhancement is performed. The complete algorithm is developed
by using a MATLAB implementation and the diagnosis in an
image can be estimated with the better accuracy and in shorter
time than previous techniques
An Automated Systems for the Detection of Macular Ischemia based-Diabetic Ret...iosrjce
The proposed methodology in this paper marks out application for automatic detection of eye
diseases called Macular Ischemia using image processing techniques. In semi urban and rural areas large
percentages of people suffer from various eye diseases. For diagnoses of various eye diseases, Image processing
technique is used. . Diseases occur in Macula from retinal images have a huge type of textures, shapes and at
times they are difficult to be recognised and identified by doctors. Thus we are trying to optimize and develop
such system which is based on smart image recognition/classification algorithms. This proposed system
provides accuracy, uniformity and speed in performance and a high credence coefficient in results interpreting.
Keywords: Macular Ischemia, diagnosis, textures, consistence
Segmentation of the Blood Vessel and Optic Disc in Retinal Images Using EM Al...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Automatic detection of optic disc and blood vessels from retinal images using...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Review of methods for diabetic retinopathy detection and severity classificationeSAT Journals
Abstract Diabetic Retinopathy is a serious vascular disorder that might lead to complete blindness. Therefore, the early detection and the treatment are necessary to prevent major vision loss. Though the Manual screening methods are available, they are time consuming and inefficient on a large image database of patients. Moreover, it demands skilled professionals for the diagnosis. Automatic Diabetic Retinopathy diagnosis systems can replace manual methods as they can significantly reduce the manual labor involved in the screening process. Screening conducted over a larger population can become efficient if the system can separate normal and abnormal cases, instead of the manual examination of all images. Therefore, Automatic Retinopathy detection systems have attracted large popularity in the recent times. Automatic retinopathy detection systems employ image processing and computer vision techniques to detect different anomalies associated with retinopathy. This paper reviews various methods of diabetic retinopathy detection and classification into different stages based on severity levels and also, various image databases used for the research purpose are discussed. Keywords— Automatic Diabetic Retinopathy detection, computer vision, Diabetic Retinopathy, image databases, image processing, manual screening
Automatic identification and classification of microaneurysms for detection o...eSAT Journals
Abstract Headlights of vehicles pose a great danger during night driving. The drivers of most vehicles use high, bright beam while driving at night. This causes a discomfort to the person travelling from the opposite direction. He experiences a sudden glare for a short period of time. This is caused due to the high intense headlight beam from the other vehicle coming towards him from the opposite direction. We are expected to dim the headlight to avoid this glare. This glare causes a temporary blindness to a person resulting in road accidents during the night. To avoid such incidents, we have fabricated a prototype of automatic headlight dimmer. This automatically switches the high beam into low beam thus reducing the glare effect by sensing the approaching vehicle. It also eliminates the requirement of manual switching by the driver which is not done at all times. The construction, working and the advantages of this prototype model is discussed in detail in this paper. Keywords: Headlight, automatic, dimmer, control, high beam, low beam, Kelvin (K).
Automatic Detection of Diabetic Maculopathy from Funduas Images Using Image A...Eman Al-dhaher
Diabetic retinopathy is a severe eye disease that affects many diabetic patients. It changes the small blood vessels in the retina resulting in loss of vision. Early detection and diagnosis have been identified as one of the ways to achieve a reduction in the percentage of visual impairment and blindness caused by diabetic retinopathy with emphasis on regular screening for detection and monitoring of this disease.
The work focuses on developing a fundus image analysis system that extracts the fundal features of the retina such as optic disk, macula (i.e., fovea) and exudates lesions (hard and soft exudates), which are the fundamental steps in an automated analyzing system to display and diagnosis diabetic retinopathy.
Vessels delineation in retinal images using COSFIRE filtersNicola Strisciuglio
George Azzopardi, Nicola Strisciuglio, Mario Vento, Nicolai Petkov - "Trainable COSFIRE filters for vessel delineation with application to retinal images”, Medical Image Analysis, Available Online 3 September 2014, DOI: 10.1016/j.media.2014.08.002
The source code of the B-COSFIRE filters is available at:
http://www.mathworks.com/matlabcentral/fileexchange/49172-trainable-cosfire-filters-for-vessel-delineation-with-application-to-retinal-images
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Detection and Grading of Diabetic Maculopathy Automatically in Digital Retina...paperpublications3
Abstract: Diabetic Retinopathy (DR) is a critical eye disease which can be regarded as manifestation of diabetes on the retina the symptoms can blur or distort the patient’s vision and are a main cause of blindness. Exudates are one of the signs of Diabetic Retinopathy. If the disease is detected early and treated promptly many of the visual loss can be prevented. This paper explains the development of an automatic fundus image processing and analytic system to facilitate diagnosis of the ophthalmologists. The algorithms to detect the optic disc; blood vessels and exudates are investigated. The proposed system extracts macula from digital retinal image using the optic disc location. Many common features such as intensity, geometric and correlations are used to distinguish between them. The system uses GLCM for feature extraction. The system uses a SVM based classifier to differentiate the retinal images in different stages of maculopathy by using the macula co-ordinates and exudates feature set.
Automatic detection of optic disc and blood vessels from retinal images using...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Review of methods for diabetic retinopathy detection and severity classificationeSAT Journals
Abstract Diabetic Retinopathy is a serious vascular disorder that might lead to complete blindness. Therefore, the early detection and the treatment are necessary to prevent major vision loss. Though the Manual screening methods are available, they are time consuming and inefficient on a large image database of patients. Moreover, it demands skilled professionals for the diagnosis. Automatic Diabetic Retinopathy diagnosis systems can replace manual methods as they can significantly reduce the manual labor involved in the screening process. Screening conducted over a larger population can become efficient if the system can separate normal and abnormal cases, instead of the manual examination of all images. Therefore, Automatic Retinopathy detection systems have attracted large popularity in the recent times. Automatic retinopathy detection systems employ image processing and computer vision techniques to detect different anomalies associated with retinopathy. This paper reviews various methods of diabetic retinopathy detection and classification into different stages based on severity levels and also, various image databases used for the research purpose are discussed. Keywords— Automatic Diabetic Retinopathy detection, computer vision, Diabetic Retinopathy, image databases, image processing, manual screening
Automatic identification and classification of microaneurysms for detection o...eSAT Journals
Abstract Headlights of vehicles pose a great danger during night driving. The drivers of most vehicles use high, bright beam while driving at night. This causes a discomfort to the person travelling from the opposite direction. He experiences a sudden glare for a short period of time. This is caused due to the high intense headlight beam from the other vehicle coming towards him from the opposite direction. We are expected to dim the headlight to avoid this glare. This glare causes a temporary blindness to a person resulting in road accidents during the night. To avoid such incidents, we have fabricated a prototype of automatic headlight dimmer. This automatically switches the high beam into low beam thus reducing the glare effect by sensing the approaching vehicle. It also eliminates the requirement of manual switching by the driver which is not done at all times. The construction, working and the advantages of this prototype model is discussed in detail in this paper. Keywords: Headlight, automatic, dimmer, control, high beam, low beam, Kelvin (K).
Automatic Detection of Diabetic Maculopathy from Funduas Images Using Image A...Eman Al-dhaher
Diabetic retinopathy is a severe eye disease that affects many diabetic patients. It changes the small blood vessels in the retina resulting in loss of vision. Early detection and diagnosis have been identified as one of the ways to achieve a reduction in the percentage of visual impairment and blindness caused by diabetic retinopathy with emphasis on regular screening for detection and monitoring of this disease.
The work focuses on developing a fundus image analysis system that extracts the fundal features of the retina such as optic disk, macula (i.e., fovea) and exudates lesions (hard and soft exudates), which are the fundamental steps in an automated analyzing system to display and diagnosis diabetic retinopathy.
Vessels delineation in retinal images using COSFIRE filtersNicola Strisciuglio
George Azzopardi, Nicola Strisciuglio, Mario Vento, Nicolai Petkov - "Trainable COSFIRE filters for vessel delineation with application to retinal images”, Medical Image Analysis, Available Online 3 September 2014, DOI: 10.1016/j.media.2014.08.002
The source code of the B-COSFIRE filters is available at:
http://www.mathworks.com/matlabcentral/fileexchange/49172-trainable-cosfire-filters-for-vessel-delineation-with-application-to-retinal-images
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Detection and Grading of Diabetic Maculopathy Automatically in Digital Retina...paperpublications3
Abstract: Diabetic Retinopathy (DR) is a critical eye disease which can be regarded as manifestation of diabetes on the retina the symptoms can blur or distort the patient’s vision and are a main cause of blindness. Exudates are one of the signs of Diabetic Retinopathy. If the disease is detected early and treated promptly many of the visual loss can be prevented. This paper explains the development of an automatic fundus image processing and analytic system to facilitate diagnosis of the ophthalmologists. The algorithms to detect the optic disc; blood vessels and exudates are investigated. The proposed system extracts macula from digital retinal image using the optic disc location. Many common features such as intensity, geometric and correlations are used to distinguish between them. The system uses GLCM for feature extraction. The system uses a SVM based classifier to differentiate the retinal images in different stages of maculopathy by using the macula co-ordinates and exudates feature set.
Discovering Abnormal Patches and Transformations of Diabetics Retinopathy in ...cscpconf
Diabetic retinopathy (DR) is one of the retinal diseases due to long-term effect of diabetes.
Early detection for diabetic retinopathy is crucial since timely treatment can prevent
progressive loss of vision. The most common diagnosis technique of diabetic retinopathy is to
screen abnormalities through retinal fundus images by clinicians. However, limited number of
well-trained clinicians increase the possibilities of misdiagnosing. In this work, we propose a
big-data-driven automatic computer-aided diagnosing (CAD) system for diabetic retinopathy
severity regression based on transfer learning, which starts from a deep convolutional neural
network pre-trained on generic images, and adapts it to large-scale DR datasets. From images
in the training set, we also automatically segment the abnormal patches with an occlusion test,
and model the transformations and deterioration process of DR. Our results can be widely used
for fast diagnosis of DR, medical education and public-level healthcare propagation.
DISCOVERING ABNORMAL PATCHES AND TRANSFORMATIONS OF DIABETICS RETINOPATHY IN ...csandit
Diabetic retinopathy (DR) is one of the retinal diseases due to long-term effect of diabetes.Early detection for diabetic retinopathy is crucial since timely treatment can prevent
progressive loss of vision. The most common diagnosis technique of diabetic retinopathy is to screen abnormalities through retinal fundus images by clinicians. However, limited number of well-trained clinicians increase the possibilities of misdiagnosing. In this work, we propose a big-data-driven automatic computer-aided diagnosing (CAD) system for diabetic retinopathy severity regression based on transfer learning, which starts from a deep convolutional neural
network pre-trained on generic images, and adapts it to large-scale DR datasets. From images in the training set, we also automatically segment the abnormal patches with an occlusion test,and model the transformations and deterioration process of DR. Our results can be widely used for fast diagnosis of DR, medical education and public-level healthcare propagation.
Automated Screening of Diabetic Retinopathy Using Image Processingiosrjce
IOSR Journal of Pharmacy and Biological Sciences(IOSR-JPBS) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of Pharmacy and Biological Science. The journal welcomes publications of high quality papers on theoretical developments and practical applications in Pharmacy and Biological Science. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Automatic Detection of Non-Proliferative Diabetic Retinopathy Using Fundus Im...iosrjce
To diagnosis of Diabetic Retinopathy (DR) it is the prime cause of blindness in the working age
population of the world. Detection method is proposed to detect dark or red lesions such as microaneurysms
and hemorrhages in fundus images.Developed during this work, this first is for collection of lesion data
information and was used by the ophthalmologist in marking images for database while the automatic
diagnosing and displaying the diagnosis result in a more friendly user interface and is as shown in chapter
three of this report. The primary aim of this project is to develop a system that will be able to identify patients
with BDR and PDR from either colour image or grey level image obtained from the retina of the patient. The
algorithm was tested fundus images. The Operating Characteristics (ROC) was determined for red spot lesion
and bleeding, while cross over points were only detected leaving further classification as part of future work
needed to complete this global project. Sensitivity and specificity was calculated for the algorithm is given
respectively as 96.3% and 95.1%
Detection of Diabetic Retinopathy using Kirsch Edge Detection and Watershed T...IJARIIT
Diabetic retinopathy (DR) is a common retinal complication associated with diabetics. A complication of diabetes is that it can also affect various parts of the body. When the small blood vessels have a high level of glucose in the retina, the vision will be blurred and can cause blindness eventually, which is known as diabetic retinopathy. However, if symptoms are identified in the early stage then proper treatment can be provided to prevent blindness. Usually the retinal images obtained from the fundus camera are examined directly and diagnosed. Due to this certain abnormalities due to diabetic retinopathy are not directly visible through the naked eye .Hence by using the image processing techniques these abnormalities can be extracted accurately and required treatments and precautions can be taken. And this also reduces the time for the ophthalmologists to detect the disease and give accurate treatments.
Automated Detection of Microaneurysm, Hard Exudates, and Cotton Wool Spots in...iosrjce
The The automatic identification of Image processing techniques for abnormalities in retinal images.
Its very importance in diabetic retinopathy screening. Manual annotations of retinal images are rare and
exclusive to obtain. The ophthalmoscope used direct analysis is a small and portable apparatus contained of a
light source and a set of lenses view the retina. The existence of diabetic retinopathy detected can be examining
the retina for its individual features. The first presence of diabetic retinopathy is the form of Microaneurysms.
This paper describes different works needed to the automatic identification of hard exudates and cotton wool
spots in retinal images for diabetic retinopathy detection and support vector machine (SVM) for classifying
images. This system is evaluated on a large dataset containing 130 retinal images. The proposed method Results
show that exudates were detected from a database with 96.9% sensitivity, specificity 96.1% and
97.38%accuracy
A Novel Approach for Diabetic Retinopthy ClassificationIJERA Editor
Sustainable Diabetic Mellitus may lead to several complications towards patients. One of the complications is
diabetic retinopathy. Diabetic retinopathy is the type of complication towards the retinal and interferes with
patient’s sight. Medical examination toward patients with diabetic retinopathy is observed directly through
retinal images using fundus camera. Diabetic retinopathy is classified into four classes based on severity, which
are: normal, non-proliferative diabetic retinopathy (NPDR), proliferative diabetic retinopathy (PDR), and
macular edema (ME). The aim of this research is to develop a method which can be used to classify the level of
severity of diabetic retinopathy based on patient’s retinal images. Seven texture features were extracted from
retinal images using gray level co-occurence matrix three dimensional method (3D-GLCM). These features are
maximum probability, correlation, contrast, energy, homogeneity, and entropy; subsequently trained using
Levenberg-Marquardt Backpropagation Neural Network (LMBP). This study used 600 data of patient’s retinal
images, consist of 450 data retinal images for training and 150 data retinal images for testing. Based on the result
of this test, the method can classify the severity of diabetic retinopathy with sensitivity of 97.37%, specificity of
75% and accuracy of 91.67%
Automatic detection of microaneurysms and hemorrhages in color eye fundus imagesijcsit
This paper presents an approach for automatic detection of microaneurysms and hemorrhages in fundus
images. These lesions are considered the earliest signs of diabetic retinopathy. The diabetic retinopathy is
a disease caused by diabetes and is considered as the major cause of blindness in working age population.
The proposed method is based on mathematical morphology and consists in removing components of
retinal anatomy to reach the lesions. This method consists of five stages: a) pre-processing; b)
enhancement of low intensity structures; c) detection of blood vessels; d) elimination of blood vessels; e)
elimination of the fovea. The accuracy of the method was tested on a public database of fundus images,
where it achieved satisfactory results, comparable to other methods from the literature, reporting 87.69%
and 92.44% of mean sensitivity and specificity, respectively.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
AKS UNIVERSITY Satna Final Year Project By OM Hardaha.pdf
C LASSIFICATION O F D IABETES R ETINA I MAGES U SING B LOOD V ESSEL A REAS
1. International Journal on Cybernetics & Informatics (IJCI) Vol. 4, No. 2, April 2015
DOI: 10.5121/ijci.2015.4224 251
CLASSIFICATION OF DIABETES RETINA IMAGES USING
BLOOD VESSEL AREA
A. S. Jadhav1
and Pushpa B. Patil2
1
Department of Electronics & Communication Engineering, B.L.D.E.A’s CET, Bijapur.
2
Department of Computer Science and Engineering, B.L.D.E.A’s CET, Bijapur.
ABSTRACT
Retina images are obtained from the fundus camera and graded by skilled professionals. However there is
considerable shortage of expert observers has encouraged computer assisted monitoring. Evaluation of
blood vessels network plays an important task in a variety of medical diagnosis. Manifestations of
numerous vascular disorders, such as diabetic retinopathy, depend on detection of the blood vessels
network. In this work the fundus RGB image is used for obtaining the traces of blood vessels and areas of
blood vessels are used for detection of Diabetic Retinopathy (DR). The algorithm developed uses
morphological operation to extract blood vessels. Mainly two steps are used: firstly enhancement operation
is applied to original retina image to remove noise and increase contrast of retinal blood vessels. Secondly
morphology operations are used to take out blood vessels. Experiments are conducted on publicly available
DIARETDB1 database. Experimental results obtained by using gray-scale images have been presented.
KEYWORDS
Blood Vessels, Fundus Images, Morphological operations.
1.INTRODUCTION
Diabetes has turn out to be one of the quickly increasing diseases worldwide. Diabetic
Retinapathy is outcome of long standing hyper glycaemia, in which retinal lesions developed that
could direct to blindness. Commonly excepted rigorous guidelines for the evaluation of biometric
authentication methods for face recognition have enabled the fast progress in the field and similar
can be likely in the medical image processing related to diabetic retinopathy detection.
Enhance in blood sugar levels linked with diabetes is the known reason of Diabetic Retinopathy
(DR). Progressive degenerative syndrome of the retina has an asymptomatic phase that can start
long before the beginning of recognized diabetes. Diabetic retinopathy is divided into various
stages. The initial signs of DR are micro aneurysms, minute hemorrhages, cotton wool spots, and
exudates that result from abnormal permeability and nonperfusion of capillaries. These early
signs are known as Nonproliferative Diabetic Retinopathy (NPDR). There may even be prior
indications of diabetic retinopathy. Fluid leaking from the retinal capillaries indicates a additional
progression of the disease, this may lead to vision Threatening Diabetic Retinopathy if the
leakage is situated in the area of most sensitive vision and is known as Nonproliferative Diabetic
Retinopathy (NPDR). Proliferative Diabetic Retinopathy (PDR) develops from occluded
capillaries that direct to retinal ischemia and formation of new vessels on the exterior of the retina
either near the optic disc or in the retinal border. It is important noting here in advance that certain
lesions representing DR, such as the number of microaneurysms and dot hemorrhages, have been
established to correlate with disease severity and likely development of the disease, such lesions
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have a reasonably well defined appearance and signify useful targets for programmed image
detection, and the detection of them provides useful information. It is also important that DR is a
treatable disease all through disease development commencing from the preclinical stage, if
detected early and treated then significant saving in cost and reduction in the progression of
vision loss is possible. As the disease is treatable, detection and monitoring of the disease via
fundus photography is beneficial and more efficient detection and monitoring saves costs. It
would seem that automated image detection of diabetic retinopathy is an engineering solution to a
increasing need.
The rest of the paper is organized as follows, Section 1 contains introduction. Section 2 provides
related work done. Section 3 describes details about proposed methodology. In section 4,
experimental results are discussed. Finally section 5 concludes the work.
2. RELATED WORK
In 2007, Al-Rawi and Karajeh [1] presented a Genetic algorithm using matched filter
optimization for computerized detection of blood vessels. Genetic algorithms and matched filters
were used to notice the fine changes in vascular structure so as to break up blood vessels from
remaining information of retina image.
In 2007, Grisam et al. [2] presented a new algorithm for the assessment of tortuosity in
vessel, recognized in digital fundus images. It is based on partitioning every vessel in part
of constant-sign curvature and then combining collectively each of evaluation of such
segments.
In 2008 Aliaa et al. [3] introduced Optic disc (OD) detection for developing computerized
screening systems for diabetic retinopathy. The OD detection algorithm was based on matching
the usual directional pattern of the retinal blood vessels. Hence, a simple matched filter is
projected to roughly match the direction of the vessels at the OD vicinity of retina image.
In 2010, Xu and Luo [4] presented a technique that uses adaptive local thresholding to produce a
binary image, and then extract bulky connected components as large vessels. The residual
fragments in binary image including some slight vessel segments were classified by support
vector machine.
In 2010, Faust et al. [5] presented algorithms for an automated recognition of diabetic retinopathy
by means of Digital Fundus images; retina images affected diabetes and normal are classified
using characteristics such as blood vessel area, exudates, hemorrhage microaneurysms and texture
extracted from retina image and supplied to the classifier.
In 2011, Vijayamadheswaran et al. [6] presented detection of diabetic retinopathy using radial
basis function. The algorithm uses features obtained from the retina images captured through
fundus camera. Contextual Clustering (CC) segmentation technique is used for classification of
retina images.
In 2012, Joshi and Karule [7] discussed Retinal Blood Vessel Segmentation. The fundus RGB
image was used for obtaining the traces of blood vessels. The algorithm generated uses
morphological operation to smoothen the background, retaining veins.
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In 2012, Selvathi et al. [8] presented computerized detection of diabetic Retinopathy for
early diagnosis using feature extraction and support vector machines. The features
considered are blood vessels, exudates & microaneurysms in training set and in test
image.
In 2013, Badsha et al. [9] presented automated method to extract the retinal blood vessel. The
proposed method comprises several basic image processing techniques, namely edge growth by
standard template, noise removal, thresholding, morphological operation and entity classification.
In 2013, Nidhal et al. [10] introduced blood vessel segmentation using mathematical morphology
in fundus retinal images. The method uses RGB retina image and separates Green channel Freon
RGB image which gives good details. Retinal images are normally noisy and non-uniform
illumination. So contrast limited adaptive histogram equalization is used for contrast
improvement. The Top-Hat transform is used for withdrawal of small details from given image.
In 2013, Kavitha and kumar [11] presented edge detection for retinal image using Superimposing
concept and Curvelet transform, which makes the edge recognition effectively. Back propagation
algorithm is used for blood vessel detection which helps to find out the real retinal blood vessels
from the image to generate the better result.
In 2013, Rashid and Shagufta [12] presented automated method to detect exudates from low
contrast images of retinopathy patient’s with non-dilated pupil using features based Fuzzy c-
means clustering method with a combination of morphology techniques & pre-processing to
improve the strength of blood vessels and optic disk detection.
In 2014, Jefrins and Sundari [13] presented Diabetic retinopathy, and also cardiovascular diseases
like ophthalmic pathologies, hypertension. The work examined the blood vessels segmentation of
two dimensional retinal images acquired from a fundus camera. Many of the techniques quoted
above have been tested on large volumes of retinal images but accurate segmentation of blood
vessel from retina image is still challenging issue.
3. PROPOSED METHODOLOGY
Accurate retinal blood vessel extraction is required for recognizing the changes in structure of
blood vessels. The components of an automatic screening system for diabetes retina are shown in
Fig.1. The proposed system is designed for retinal blood vessels segmentation and computation of
blood vessel area for monitoring the changes in blood vessels due to diabetics.
• RGB to Gray: RGB retina image acquired through fundus camera is converted into a gray-
scale image in order to make easy computations and decrease the size of data and
computational time. All input image size is resized to 256x256 to consider uniform areas.
• Contrast Enhancement: Low contrast images could occur often due to many reasons, such
as poor or non-uniform illumination condition, nonlinearity or small active range of the
imaging sensor, i.e., illumination is distributed non-uniformly within the image. Therefore, it
is needed to increase the contrast of these images to provide a better transform representation
for succeeding image analysis steps. Contrast Limited Adaptive Histogram Equalization
(CLAHE) technique is adopted to perform the contrast improvement
• Image Segmentation: The size and shape of the structuring element affects the number of
pixels being added or removed from the object in the image. Closing operation is defined as
dilation (Max filter) followed by erosion (Min filter).Dilation is an function that grows or
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thickens things in a binary image. Dilation in gray scale enlarges brighter regions and closes
small dark regions. The erosion is needed to shrink the dilated objects back to their original
size and shape. The dark regions closed by dilation do not react to erosion. Thus, the vessels
being thin dark segments laid out on a brighter background are closed by a closing operation.
The image through smoothing filter is input for the edge detection technique. The results of
edge detection is compared with the image passing before and after the smoothing filter and
results are found better for the Canny’s edge detection technique.
• Thresholding and Background Exclusion: The main purpose of this step is to remove
background variations in illumination from an image so that the foreground objects may be
more easily seen. This produces a binary image in which the value of each pixel is either 1 or
0
Fig.1. Block diagram for the Proposed Model
• Morphological Closing: Closing of set A by structuring element B is denoted by A
● B and is given by equation (1).
A ● B = (A ϴ B) ϴ B (1)
In this step we apply morphological closing process with disk as structuring element.
The size of the structure element square is chosen as 10 to turn characters and other small
shapes with foreground to background color.
• Noise removal: This step applies median filter to remove non-blood vessel part in the
retina image. It keeps much of the blood vessel part as it is in the retina image (white) and
converts remaining part of the retina into background black.
4. RESULTS AND DISCUSSION
The data base description, evaluation procedure and results are discussed in the following section.
Input RGB Fundus Retina Image
Gray Scale Conversion
Morphological Operation
Segmentation
Extraction of Blood Vessels
Finding Area of Blood Vessels
Classifying the Input Image as
Diabetic or normal
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4.1 Database description
Proposed system uses a database of dedicatedly selected high quality medical images which are
representatives of the problem and have been verified by experts. A database DIARETDB1 is
used which consists of 89 color fundus images of which 84 contain diabetic signs and 5 are
normal.
4.2 Evaluation Procedure
In medical analysis, the medical inputs patient’s data is usually classified into two classes, that is
the disease is found or not. The classification precision of diagnosis is assessed using sensitivity
specificity measures. Sensitivity is the measure used to find percentage of correctly identified
diabetic retina images from database and specificity pertains to percentage non-diabetic images
detected from the database. These parameters are computed using equation (2) and (3)
respectively.
Where TP is number of abnormal images dtermined as abnormal, TN is number of normal images
found as normal, FN is number of abnormal images found as normal and FP is number of normal
images found as abnormal.
Fig.2 (a) and (b) Shows some sample fundus retina images used for testing and their blood vessels
extracted from corresponding input retina image. The test retina image which is to be classified as
diabetic or non-diabetic is given as input and we get the blood vessels separated from other
contents of retina image as shown in Fig.2. Further the areas of blood vessels are computed and
based on computed values of blood vessel areas the retina images are classified as diabetic or
non- diabetic. Total 89 Retina images are tested out of which 80 images are classified correctly
and 9 images are classified incorrectly because of low quality input image.
(a) Input retina images used for testing
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(b) Results of blood vessel extraction
Fig 2. Blood vessels extracted from input images
The Table 1 shows the results of classification of retina images of database DIARETDB1 in terms
of sensitivity and specificity
Table 1.Classification results of retina images
Total
Images in
the
database
Correctly
classified
Images
Incorrectly
classified
Images
% of
sensitivity
% of
specificity
89 80 9 90 90
5. CONCLUSION
The methods presented in the paper are based on morphological operations and tested for large
number of images. The projected method for blood vessels detection based on mathematical
morphological operation is simple and robust in representing the directional model of the retinal
vessels surrounding the optic disk. The method developed here is simple and computationally
efficient for retinal blood vessel segmentation, which gives good information about presence of
diabetes and classification of retina images.
REFERENCES
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[3] Aliaa Abdel-Haleim Abdel-Razik Youssif, Atef Zaki Ghalwash, and Amr Ahmed Sabry Abdel-
Rahman Ghoneim: Optic disc (OD) detection for developing automated screening systems for
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[4] Xu, L and S.Luo: A novel method for blood vessel detection from retinal images. Biomed.Eng.,9:14-
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[5] Oliver Faust, Rajendra Acharya U.E.Y.K.Ng.kwan-Hoong Ng. Jasjit S. Suri: Algorithms for the
automated detection of diabetic retinopathy using Digital Fundus images. A review,” Springer
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[6] Mr. R. Vijayamadheswaran, Dr.M.Arthanari, Mr.M.Sivakumar: Detection of diabetic retinopathy
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[8] Selvathi D, N.B. prakash and Neethi Balagopal, “Automated detection of diabetic Retinopathy for
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AUTHORS
Dr. Pushpa B. Patil received Ph.D from S.R.T.M. University, Nanded, Maharastra,
M.Tech.(CSE) from Visveshwaraya Technological University Belgaum and B.E.(CSE)
from Karnataka University Darawad, India. From 1997-2000, she worked as lecturer in
Computer Science Department at MBE’s Engineering College, Ambajogai, Maharastra,
India. In 2000, she joined as a lecturer in the Department of Computer Science at B. L. D.
E’ s. Institute of Engineering and Technology, Bijapur, Karnataka, India. Presently she is
serving as Professor and Head of the Department of Computer Science and Engineering.
Her research interests include image processing, pattern recognition, and relevance feedback in Content
Based Image Retrieval. She is also life member of Indian Society for Technical Education and Institute of
Engineers. She has published more than 17 research papers in international conferences and journals.
Mr. Ambaji S. Jadhav has received B.E (E&C) and M.Tech (CSE) from Visvesvaraya
Technological University, Belagavi. He has an experience of 12 years and his area of
interest are image processing, pattern recognition and signal processing. Currently
pursuing Ph.D under Visvesvaraya Technological University.