This document presents research on segmenting the optic disk and retinal vessels in fundus images. It describes an algorithm that first applies anisotropic diffusion filtering and thresholding to enhance and extract the retinal vessel network. A graph cut method is then used to segment the optic disk, using either an MRF image reconstruction method or compensation factor method to address overlap of vessels into the optic disk region. The MRF method reconstructs the image in the optic disk region to remove vessels before segmentation, while the compensation factor incorporates local intensity characteristics of vessels. Experimental results on fundus images demonstrate the algorithm can accurately segment the optic disk and retinal vessels.
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
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
Abstract— The division is the urgent stage in iris acknowledgment. We have utilized the worldwide limit an incentive for division. In the above calculation we have not considered the eyelid and eyelashes relics, which corrupt the execution of iris acknowledgment framework. The framework gives sufficient execution likewise the outcomes are attractive. Assist advancement of this technique is under way and the outcomes will be accounted for sooner rather than later. Based on the reasonable peculiarity of the iris designs we can anticipate that iris acknowledgment framework will turn into the main innovation in personality verification.In this paper, iris acknowledgment calculation is depicted. As innovation advances and data and scholarly properties are needed by numerous unapproved work force. Therefore numerous associations have being scanning routes for more secure confirmation strategies for the client get to. The framework steps are catching iris designs; deciding the area of iris limits; changing over the iris limit to the binarized picture; The framework has been actualized and tried utilizing dataset of number of tests of iris information with various complexity quality.
Keywords— GAC, Iris Recognition, Iris Segmentation, Snakes.
Proposition of local automatic algorithm for landmark detection in 3D cephalo...journalBEEI
This study proposes a new contribution to solve the problem of automatic landmarks detection in three-dimensional cephalometry. 3D images obtained from CBCT (cone beam computed tomography) equipment were used for automatic identification of twelve landmarks. The proposed method is based on a local geometry and intensity criteria of skull structures. After the step of preprocessing and binarization, the algorithm segments the skull into three structures using the geometry information of nasal cavity and intensity information of the teeth. Each targeted landmark was detected using local geometrical information of the volume of interest containing this landmark. The ICC and confidence interval (95% CI) for each direction were 0, 91 (0.75 to 0.96) for x- direction; 0.92 (0.83 to 0.97) for y-direction; 0.92 (0.79 to 0.97) for z-direction. The mean error of detection was calculated using the Euclidian distance between the 3D coordinates of manually and automatically detected landmarks. The overall mean error of the algorithm was 2.76 mm with a standard deviation of 1.43 mm. Our proposed approach for automatic landmark identification in 3D cephalometric was capable of detecting 12 landmarks on 3D CBCT images which can be facilitate the use of 3D cephalometry to orthodontists.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
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
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
Abstract— The division is the urgent stage in iris acknowledgment. We have utilized the worldwide limit an incentive for division. In the above calculation we have not considered the eyelid and eyelashes relics, which corrupt the execution of iris acknowledgment framework. The framework gives sufficient execution likewise the outcomes are attractive. Assist advancement of this technique is under way and the outcomes will be accounted for sooner rather than later. Based on the reasonable peculiarity of the iris designs we can anticipate that iris acknowledgment framework will turn into the main innovation in personality verification.In this paper, iris acknowledgment calculation is depicted. As innovation advances and data and scholarly properties are needed by numerous unapproved work force. Therefore numerous associations have being scanning routes for more secure confirmation strategies for the client get to. The framework steps are catching iris designs; deciding the area of iris limits; changing over the iris limit to the binarized picture; The framework has been actualized and tried utilizing dataset of number of tests of iris information with various complexity quality.
Keywords— GAC, Iris Recognition, Iris Segmentation, Snakes.
Proposition of local automatic algorithm for landmark detection in 3D cephalo...journalBEEI
This study proposes a new contribution to solve the problem of automatic landmarks detection in three-dimensional cephalometry. 3D images obtained from CBCT (cone beam computed tomography) equipment were used for automatic identification of twelve landmarks. The proposed method is based on a local geometry and intensity criteria of skull structures. After the step of preprocessing and binarization, the algorithm segments the skull into three structures using the geometry information of nasal cavity and intensity information of the teeth. Each targeted landmark was detected using local geometrical information of the volume of interest containing this landmark. The ICC and confidence interval (95% CI) for each direction were 0, 91 (0.75 to 0.96) for x- direction; 0.92 (0.83 to 0.97) for y-direction; 0.92 (0.79 to 0.97) for z-direction. The mean error of detection was calculated using the Euclidian distance between the 3D coordinates of manually and automatically detected landmarks. The overall mean error of the algorithm was 2.76 mm with a standard deviation of 1.43 mm. Our proposed approach for automatic landmark identification in 3D cephalometric was capable of detecting 12 landmarks on 3D CBCT images which can be facilitate the use of 3D cephalometry to orthodontists.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
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
Glaucoma is a chronic eye disease in which the optic nerve head is progressively damaged which leads to loss of
vision. Early diagnosis and treatment is the key to preserving sight in people with glaucoma. Current tests using
intraocular pressure (IOP) are not sensitive enough for population based glaucoma screening. Assessment of the
damaged optic nerve head is both more promising, and superior to IOP measurement or visual field testing. This paper
presents superpixel classification based optic disc and optic cup segmentation for glaucoma screening. In optic disc
segmentation, histograms and centre surround statistics are used to classify each superpixel as disc or non-disc. For optic
cup segmentation, in addition to the histograms and centre surround statistics, the location information is also included
into the feature space to boost the performance. The segmented optic disc and optic cup are used to compute the CDR
for glaucoma screening. The Cup to Disc Ratio (CDR) of the color retinal fundus camera image is the primary identifier
to confirm Glaucoma given patient.
Keywords — IOP measurement, optic cup segmentation, optic disc segmentation, CDR.
Glaucoma Screening Test By Segmentation of Optical Disc& Cup Segmentation Usi...IJERA Editor
Glaucoma is one of the most common causes of blindness and it is becoming even more important considering
the ageing society. Because healing of died retinal nerve fibers is not possible early detection and prevention is
essential. Robust, automated mass-screening will help to extend the symptom-free life of affected patients. We
devised a novel, automated, appearance based glaucoma classification system that does not depend on
segmentation based measurements. Our purely data-driven approach is applicable in large-scale screening
examinations. The proposed segmentation methods have been evaluated in a database of 650 images with optic
disc and optic cup boundaries manually marked by trained professionals. Our expected Experimental results
may be average overlapping error of 9.5% and 24.1% in optic disc and optic cup segmentation, respectively.
Segmentation of Blood Vessels and Optic Disc in Retinal Imagesresearchinventy
Retinal image analysis is increasingly prominent as a non-intrusive diagnosis method in modern ophthalmology. In this paper, we present a novel method to segment blood vessels and optic disc in the fundus retinal images. The method could be used to support non-intrusive diagnosis in modern ophthalmology since the morphology of the blood vessel and the optic disc is an important indicator for diseases like diabetic retinopathy, glaucoma and hypertension. Our method takes as first step the extraction of the retina vascular tree using the graph cut technique. The blood vessel information is then used to estimate the location of the optic disc. The optic disc segmentation is performed using two alternative methods. The Markov Random Field (MRF) image reconstruction method segments the optic disc by removing vessels from the optic disc region and the Compensation Factor method segments the optic disc using prior local intensity knowledge of the vessels. The proposed method is tested on three public data sets, DIARETDB1, DRIVE and STARE. The results and comparison with alternative methods show that our method achieved exceptional performance in segmenting the blood vessel and optic disc.
Automated Detection of Optic Disc in Retinal FundusImages Using PCAiosrjce
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.
Teamed with 2 students to research and implement the automation of diagnosis of Diabetic Retinopathy and co-ordinated with an Ophthalmologist to verify our implementation.
Responsibilities included MATLAB coding, algorithm testing, and product documentation.
• Automation in MATLAB involving retinal image analysis to help
Ophthalmologist increase the productivity and efficiency in a clinical
environment.
• Used Image Processing concepts such as Hough Transform, Bottom Hat
Transform, Edge Detection Technique and Morphological Operators.
Provided our algorithm and documentation to our research faculty advisor to enable him to continue this research to the next phase.
IMAGE PROCESSING Projects for M. Tech, IMAGE PROCESSING Projects in Vijayanagar, IMAGE PROCESSING Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, IMAGE PROCESSING IEEE projects in Bangalore, IEEE 2015 IMAGE PROCESSING Projects, MATLAB Image Processing Projects, MATLAB Image Processing Projects in Bangalore, MATLAB Image Processing Projects in Vijayangar
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.
Research on Iris Region Localization AlgorithmsIJERA Editor
Iris recognition is a biometric technique that offers premium performance. Iris localization is critical to the success of an iris recognition system, since data that is falsely represented as iris pattern data will corrupt the biometric templates generated, resulting in poor recognition rates. So far different algorithms for iris localization having been proposed. This paper explored four efficient methods for iris localization, out of these three methods of iris localization in circular form and one methods of unwrapping the iris in to a flat bed. Experimental results are reported to demonstrate performance evaluation of every implemented algorithms. Conclusion based on comparisons can provide most significant information for further research. A CASIA and UPOL iris databases of iris images has been used for implementation of iris localization General Term Biometrics,Iris Recognition,Iris Localization
A UTOMATIC C OMPUTATION OF CDR U SING F UZZY C LUSTERING T ECHNIQUEScsandit
Eye disease identification techniques are highly im
portant in the field of ophthalmology. A
vertical Cup-to-Disc Ratio which is the ratio of th
e vertical diameter of the optic cup to that of
the optic disc, of the fundus eye image is one of t
he important signs of glaucoma. This paper
presents an automated method for the extraction of
optic disc and optic cup using Fuzzy C
Means clustering technique. The validity of this ne
w method has been tested on 454 colour
fundus images from
three different publicly available databases DRION,
DIARATDB0 and
DIARETDB1 and, images from an ophthalmologist. The
average success rate of optic disc and
optic cup segmentation is 94.26percentage. The scat
ter plot depicts high positive correlation
between clinical CDR and the CDR obtained using the
new method. The result of the system
seems to be promising and useful for clinical work.
The optic disc (OD) is one of the important part of the eye for detecting various diseases such as Diabetic Retinopathy and Glaucoma. The localization of optic disc is extremely important for determining hard exudates and lesions. Diagnosis of the disease can prevent people from vision loss. This paper analyzes various techniques which are proposed by different authors for the exact localization of optic disc to prevent vision loss.
INVIVO PATTERN RECOGNITION AND DIGITAL IMAGE ANALYSIS OF SHEAR STRESS DISTRIB...IJCI JOURNAL
Human eye is made of a number of structural components to deliver vision, and cornea is the front window of the eye. Human cornea is made of soft biological materials. It is unfriendly for exposures to the common energy levels of X-ray scans for repeated probing of its structural architecture. Here we study an alternative imaging methodology by using a normal white-light source. By exploiting the natural birefringent property of cornea, the shear stress distribution pattern and its directional characteristics on the surface of cornea is recognized in vivo. Digital image processing of corneal retardation helps us to locate the stress concentration zones on its surface and to study their features along preferential directions. Such digital image outputs could be used in future to bench mark the health standard of cornea as well as a potential identity signature of people’s eyes.
A novel equalization scheme for the selective enhancement of optical disc and...TELKOMNIKA JOURNAL
The ratio of the diameters of Optic Cup (OC) and Optic Disc (OD), termed as ‘Cup to Disc Ratio’
(CDR), derived from the fundus imagery is a popular biomarker used for the diagnosis of glaucoma.
Demarcation of OC and OD either manually or through automated image processing algorithms is error
prone because of poor grey level contrast and their vague boundaries. A dedicated equalization which
simultaneously compresses the dynamic range of the background and stretches the range of ODis
proposed in this paper. Unlike the conventional GHE, in the proposed equalization, the original histogram
is inverted and weighted nonlinearly before computing the Cumulative Probability Density (CPD).
The equalization scheme is compared with Adaptive Histogram Equalization (AHE), Global Histogram
Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) in terms of the
difference between the mean grey levels of OD and the background, using a quantitative metric known as
Contrast Improvement Index (CII). The CII exhibited by CLAHE, GHE and the proposed scheme are
1.1977 ± 0.0326, 1.0862 ± 0.0304 and 1.3312 ± 0.0486, respectively.The proposed method is observed to
be superior to CLAHE, GHE and AHE and it can be employed in Computerized Clinical Decision Support
Systems (CCDSS) to improve the accuracy of localizing the OD and the computation of CDR.
Retinal blood vessel extraction and optical disc removaleSAT Journals
Abstract Retinal image processing is an important process by which we can detect the blood vessels and this helps us in detecting the DIABETIC RETINOPATHY at a early stage and this is very helpful because the symptoms are not known by anyone unless we have blur eye sight or we get blind. And this mainly occurs in people suffering from high diabetes. So by extracting the blood vessels using the algorithm we can see which blood vessels are actually damaged. So by using the algorithm we can continuously survey the situation and can protect our eye-sight. Keywords: field of view, retinopathy, thresholding, morphology, Otsu's algorithm, MATLAB.
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
Glaucoma is a chronic eye disease in which the optic nerve head is progressively damaged which leads to loss of
vision. Early diagnosis and treatment is the key to preserving sight in people with glaucoma. Current tests using
intraocular pressure (IOP) are not sensitive enough for population based glaucoma screening. Assessment of the
damaged optic nerve head is both more promising, and superior to IOP measurement or visual field testing. This paper
presents superpixel classification based optic disc and optic cup segmentation for glaucoma screening. In optic disc
segmentation, histograms and centre surround statistics are used to classify each superpixel as disc or non-disc. For optic
cup segmentation, in addition to the histograms and centre surround statistics, the location information is also included
into the feature space to boost the performance. The segmented optic disc and optic cup are used to compute the CDR
for glaucoma screening. The Cup to Disc Ratio (CDR) of the color retinal fundus camera image is the primary identifier
to confirm Glaucoma given patient.
Keywords — IOP measurement, optic cup segmentation, optic disc segmentation, CDR.
Glaucoma Screening Test By Segmentation of Optical Disc& Cup Segmentation Usi...IJERA Editor
Glaucoma is one of the most common causes of blindness and it is becoming even more important considering
the ageing society. Because healing of died retinal nerve fibers is not possible early detection and prevention is
essential. Robust, automated mass-screening will help to extend the symptom-free life of affected patients. We
devised a novel, automated, appearance based glaucoma classification system that does not depend on
segmentation based measurements. Our purely data-driven approach is applicable in large-scale screening
examinations. The proposed segmentation methods have been evaluated in a database of 650 images with optic
disc and optic cup boundaries manually marked by trained professionals. Our expected Experimental results
may be average overlapping error of 9.5% and 24.1% in optic disc and optic cup segmentation, respectively.
Segmentation of Blood Vessels and Optic Disc in Retinal Imagesresearchinventy
Retinal image analysis is increasingly prominent as a non-intrusive diagnosis method in modern ophthalmology. In this paper, we present a novel method to segment blood vessels and optic disc in the fundus retinal images. The method could be used to support non-intrusive diagnosis in modern ophthalmology since the morphology of the blood vessel and the optic disc is an important indicator for diseases like diabetic retinopathy, glaucoma and hypertension. Our method takes as first step the extraction of the retina vascular tree using the graph cut technique. The blood vessel information is then used to estimate the location of the optic disc. The optic disc segmentation is performed using two alternative methods. The Markov Random Field (MRF) image reconstruction method segments the optic disc by removing vessels from the optic disc region and the Compensation Factor method segments the optic disc using prior local intensity knowledge of the vessels. The proposed method is tested on three public data sets, DIARETDB1, DRIVE and STARE. The results and comparison with alternative methods show that our method achieved exceptional performance in segmenting the blood vessel and optic disc.
Automated Detection of Optic Disc in Retinal FundusImages Using PCAiosrjce
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.
Teamed with 2 students to research and implement the automation of diagnosis of Diabetic Retinopathy and co-ordinated with an Ophthalmologist to verify our implementation.
Responsibilities included MATLAB coding, algorithm testing, and product documentation.
• Automation in MATLAB involving retinal image analysis to help
Ophthalmologist increase the productivity and efficiency in a clinical
environment.
• Used Image Processing concepts such as Hough Transform, Bottom Hat
Transform, Edge Detection Technique and Morphological Operators.
Provided our algorithm and documentation to our research faculty advisor to enable him to continue this research to the next phase.
IMAGE PROCESSING Projects for M. Tech, IMAGE PROCESSING Projects in Vijayanagar, IMAGE PROCESSING Projects in Bangalore, M. Tech Projects in Vijayanagar, M. Tech Projects in Bangalore, IMAGE PROCESSING IEEE projects in Bangalore, IEEE 2015 IMAGE PROCESSING Projects, MATLAB Image Processing Projects, MATLAB Image Processing Projects in Bangalore, MATLAB Image Processing Projects in Vijayangar
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.
Research on Iris Region Localization AlgorithmsIJERA Editor
Iris recognition is a biometric technique that offers premium performance. Iris localization is critical to the success of an iris recognition system, since data that is falsely represented as iris pattern data will corrupt the biometric templates generated, resulting in poor recognition rates. So far different algorithms for iris localization having been proposed. This paper explored four efficient methods for iris localization, out of these three methods of iris localization in circular form and one methods of unwrapping the iris in to a flat bed. Experimental results are reported to demonstrate performance evaluation of every implemented algorithms. Conclusion based on comparisons can provide most significant information for further research. A CASIA and UPOL iris databases of iris images has been used for implementation of iris localization General Term Biometrics,Iris Recognition,Iris Localization
A UTOMATIC C OMPUTATION OF CDR U SING F UZZY C LUSTERING T ECHNIQUEScsandit
Eye disease identification techniques are highly im
portant in the field of ophthalmology. A
vertical Cup-to-Disc Ratio which is the ratio of th
e vertical diameter of the optic cup to that of
the optic disc, of the fundus eye image is one of t
he important signs of glaucoma. This paper
presents an automated method for the extraction of
optic disc and optic cup using Fuzzy C
Means clustering technique. The validity of this ne
w method has been tested on 454 colour
fundus images from
three different publicly available databases DRION,
DIARATDB0 and
DIARETDB1 and, images from an ophthalmologist. The
average success rate of optic disc and
optic cup segmentation is 94.26percentage. The scat
ter plot depicts high positive correlation
between clinical CDR and the CDR obtained using the
new method. The result of the system
seems to be promising and useful for clinical work.
The optic disc (OD) is one of the important part of the eye for detecting various diseases such as Diabetic Retinopathy and Glaucoma. The localization of optic disc is extremely important for determining hard exudates and lesions. Diagnosis of the disease can prevent people from vision loss. This paper analyzes various techniques which are proposed by different authors for the exact localization of optic disc to prevent vision loss.
INVIVO PATTERN RECOGNITION AND DIGITAL IMAGE ANALYSIS OF SHEAR STRESS DISTRIB...IJCI JOURNAL
Human eye is made of a number of structural components to deliver vision, and cornea is the front window of the eye. Human cornea is made of soft biological materials. It is unfriendly for exposures to the common energy levels of X-ray scans for repeated probing of its structural architecture. Here we study an alternative imaging methodology by using a normal white-light source. By exploiting the natural birefringent property of cornea, the shear stress distribution pattern and its directional characteristics on the surface of cornea is recognized in vivo. Digital image processing of corneal retardation helps us to locate the stress concentration zones on its surface and to study their features along preferential directions. Such digital image outputs could be used in future to bench mark the health standard of cornea as well as a potential identity signature of people’s eyes.
A novel equalization scheme for the selective enhancement of optical disc and...TELKOMNIKA JOURNAL
The ratio of the diameters of Optic Cup (OC) and Optic Disc (OD), termed as ‘Cup to Disc Ratio’
(CDR), derived from the fundus imagery is a popular biomarker used for the diagnosis of glaucoma.
Demarcation of OC and OD either manually or through automated image processing algorithms is error
prone because of poor grey level contrast and their vague boundaries. A dedicated equalization which
simultaneously compresses the dynamic range of the background and stretches the range of ODis
proposed in this paper. Unlike the conventional GHE, in the proposed equalization, the original histogram
is inverted and weighted nonlinearly before computing the Cumulative Probability Density (CPD).
The equalization scheme is compared with Adaptive Histogram Equalization (AHE), Global Histogram
Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) in terms of the
difference between the mean grey levels of OD and the background, using a quantitative metric known as
Contrast Improvement Index (CII). The CII exhibited by CLAHE, GHE and the proposed scheme are
1.1977 ± 0.0326, 1.0862 ± 0.0304 and 1.3312 ± 0.0486, respectively.The proposed method is observed to
be superior to CLAHE, GHE and AHE and it can be employed in Computerized Clinical Decision Support
Systems (CCDSS) to improve the accuracy of localizing the OD and the computation of CDR.
Retinal blood vessel extraction and optical disc removaleSAT Journals
Abstract Retinal image processing is an important process by which we can detect the blood vessels and this helps us in detecting the DIABETIC RETINOPATHY at a early stage and this is very helpful because the symptoms are not known by anyone unless we have blur eye sight or we get blind. And this mainly occurs in people suffering from high diabetes. So by extracting the blood vessels using the algorithm we can see which blood vessels are actually damaged. So by using the algorithm we can continuously survey the situation and can protect our eye-sight. Keywords: field of view, retinopathy, thresholding, morphology, Otsu's algorithm, MATLAB.
AN AUTOMATIC SCREENING METHOD TO DETECT OPTIC DISC IN THE RETINAijait
The location of Optic Disc (OD) is of critical importance in retinal image analysis. This research paper carries out a new automated methodology to detect the optic disc (OD) in retinal images. OD detection helps the ophthalmologists to find whether the patient is affected by diabetic retinopathy or not. The proposed technique is to use line operator which gives higher percentage of detection than the already existing methods. The purpose of this project is to automatically detect the position of the OD in digital retinal fundus images. The method starts with converting the RGB image input into its LAB component. This image is smoothed using bilateral smoothing filter. Further, filtering is carried out using line operator. After which gray orientation and binary map orientation is carried out and then with the use of the resulting maximum image variation the area of the presence of the OD is found. The portions other
than OD are blurred using 2D circular convolution. On applying mathematical steps like peak classification, concentric circles design and image difference calculation, OD is detected. The proposed method was evaluated using a subset of the STARE project’s dataset and the success percentage was found
to be 96%.
Binary operation based hard exudate detection and fuzzy based classification ...IJECEIAES
Diabetic retinopathy (DR) is one of the most considerable reasons for visual impairment. The main objective of this paper is to automatically detect and recognize DR lesions like hard exudates, as it helps in diagnosing and screening of the disease. Here, binary operation based image processing for detecting lesions and fuzzy logic based extraction of hard exudates on diabetic retinal images are discused. In the initial stage, the binary operations are used to identify the exudates. Similarly, the RGB channel space of the DR image is used to create fuzzy sets and membership functions for extracting the exudates. The membership directives obtained from the fuzzy rule set are used to detect the grade of exudates. In order to evaluate the proposed approach, experiment tests are carriedout on various set of images and the results are verified. From the experiment results, the sensitivity obtained is 98.10%, specificity is 96.96% and accuracy is 98.2%. These results suggest that the proposed method could be a diagnostic aid for ophthalmologists in the screening for DR.
Optic Disc and Macula Localization from Retinal Optical Coherence Tomography ...IJECEIAES
This research used images from Optical Coherence Tomography (OCT) examination as well as fundus images to localize the optical disc and macular layer of retina. The researchers utilized the OCT and fundus image to interpret the distance between macular center and optic disc in the image. The distance will express the area of macula that can be employed for further research. This distance could recognize the thickness of macula parameters diameter that will be used in localizing process of optic disc and macula. The parameters are the circle radius, the size of window’s filter, the constant value and the size of optic disc element structure as well as the size of macula. The results of this study are expected to improve the accuracy of macula detection that experience the edema.
AUTOMATED SEGMENTATION OF FLUORESCENT AND FUNDS IMAGES BASED ON RETINAL BLOOD...acijjournal
ABSTRACT
Measurements of retinal blood vessel morphology have been shown to be related to the risk of cardiovascular diseases. The wrong identification of vessels may result in a large variation of these measurements, leading to a wrong clinical diagnosis. In this paper, we address the problem of automatically identifying true vessels as a post processing step to vascular structure segmentation. We model the segmented vascular structure as a vessel segment graph and formulate the problem of identifying vessels as one of finding the optimal forest in the graph given a set of constraints. We design a method to solve this optimization problem and evaluate it on a large real-world dataset of 2,446 retinal images. Experiment results are analyzed with respect to actual measurements of vessel morphology. The results show that the proposed approach is able to achieve 98.9% pixel precision and 98.7% recall of the true vessels for clean segmented retinal images, and remains robust even when the segmented image is noisy.
AUTOMATED SEGMENTATION OF FLUORESCENT AND FUNDS IMAGES BASED ON RETINAL BLOOD...acijjournal
Measurements of retinal blood vessel morphology have been shown to be related to the risk of
cardiovascular diseases. The wrong identification of vessels may result in a large variation of these
measurements, leading to a wrong clinical diagnosis. In this paper, we address the problem of
automatically identifying true vessels as a post processing step to vascular structure segmentation. We
model the segmented vascular structure as a vessel segment graph and formulate the problem of identifying
vessels as one of finding the optimal forest in the graph given a set of constraints. We design a method to
solve this optimization problem and evaluate it on a large real-world dataset of 2,446 retinal images.
Experiment results are analyzed with respect to actual measurements of vessel morphology. The results
show that the proposed approach is able to achieve 98.9% pixel precision and 98.7% recall of the true
vessels for clean segmented retinal images, and remains robust even when the segmented image is noisy.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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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.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.