36 research outputs found
Detection of retinal blood vessels from ophthalmoscope images using morphological approach
Accurate segmentation of retinal blood vessels is an essential task for diagnosis of various pathological disorders. In this paper, a novel method has been introduced for segmenting retinal blood vessels which involves pre-processing, segmentation and post-processing. The pre-processing stage enhanced the image using contrast limited adaptive histogram equalization and 2D Gabor wavelet. The enhanced image is segmented using geodesic operators and a final segmentation output is obtained by applying a post-processing stage that involves hole filling and removal of isolated pixels. The performance of the proposed method is evaluated on the publicly available Digital retinal images for vessel extraction (DRIVE) and High-resolution fundus (HRF) databases using five different measurements and experimental analysis shows that the proposed method reach an average accuracy of 0.9541 on DRIVE database and 0.9568, 0.9478 and 0.9613 on HRF database with healthy, diabetic retinopathy (DR) and glaucomatous images respectively
A thresholding based technique to extract retinal blood vessels from fundus images
Retinal imaging has become the significant tool among all the medical imaging technology, due to its capability to extract many data which is linked to various eye diseases. So, the accurate extraction of blood vessel is necessary that helps the eye care specialists and ophthalmologist to identify the diseases at the early stages. In this paper, we have proposed a computerized technique for extraction of blood vessels from fundus images. The process is conducted in three phases: (i) pre-processing where the image is enhanced using contrast limited adaptive histogram equalization and median filter, (ii) segmentation using mean-C thresholding to extract retinal blood vessels, (iii) post-processing where morphological cleaning operation is used to remove isolated pixels. The performance of the proposed method is tested on and experimental results show that our method achieve an accuracies of 0.955 and 0.954 on Digital retinal images for vessel extraction (DRIVE) and Child heart and health study in England (CHASE_DB1) databases respectively
Retinal Blood Vessel Extraction from Fundus Images Using Enhancement Filtering and Clustering
Screening of vision troubling eye diseases by segmenting fundus images eases the danger of loss of sight of people. Computer assisted analysis can play an important role in the forthcoming health care system universally. Therefore, this paper presents a clustering based method for extraction of retinal vasculature from ophthalmoscope images. The method starts with image enhancement by contrast limited adaptive histogram equalization (CLAHE) from which feature extraction is accomplished using Gabor filter followed by enhancement of extracted features with Hessian based enhancement filters. It then extracts the vessels using K-mean clustering technique. Finally, the method ends with the application of a morphological cleaning operation to get the ultimate vessel segmented image. The performance of the proposed method is evaluated by taking two different publicly available Digital retinal images for vessel extraction (DRIVE) and Child heart and health study in England (CHASE_DB1) databases using nine different performance matrices. It gives average accuracies of 0.952 and 0.951 for DRIVE and CHASE_DB1 databases, respectively.
Detection of retinal blood vessels from ophthalmoscope images using morphological approach
Accurate segmentation of retinal blood vessels is an essential task for diagnosis of various pathological disorders. In this paper, a novel method has been introduced for segmenting retinal blood vessels which involves pre-processing, segmentation and post-processing. The pre-processing stage enhanced the image using contrast limited adaptive histogram equalization and 2D Gabor wavelet. The enhanced image is segmented using geodesic operators and a final segmentation output is obtained by applying a post-processing stage that involves hole filling and removal of isolated pixels. The performance of the proposed method is evaluated on the publicly available Digital retinal images for vessel extraction (DRIVE) and High-resolution fundus (HRF) databases using five different measurements and experimental analysis shows that the proposed method reach an average accuracy of 0.9541 on DRIVE database and 0.9568, 0.9478 and 0.9613 on HRF database with healthy, diabetic retinopathy (DR) and glaucomatous images respectively
Not Available
Not AvailableWatershed is generally considered as the smallest unit to get hydrological response of any
developmental activity. To work out a comprehensive development plan for optimum use
of natural resources the study of watershed characteristics is necessary. Watershed
characteristics can be understood from the morphometric analysis and which can be better
analyzed by GIS. The aim of the present study is to understand the morphometric
characteristics of Katra watershed of Koraput, Odisha, situated in part of Eastern Ghats, an
ecologically sensitive region using GIS. The drainage area of Katra watershed is 34 km
and the drainage pattern is dendritic to sub-dendritic. The slope of the watershed varied
from 0 to 82 % and the slope variation is chiefly controlled by the local geomorphology
and erosion cycles. The watershed was classified as a forth order drainage basin and the
controlling factors of the stream orders are physiography, rainfall, local lithology and
structure. The lower order streams are mostly dominating in the watershed. Lithological,
structural and geomorphological expression of the watershed controls the flow direction of
the entire drainage network. The increase in stream length ratio from lower to higher order
is an indication of geomorphically mature watershed. The work will be the input to
evaluate the basin hydrology, water resources, and input and output components in the
hydrology cycle.Not Availabl
Not Available
Not AvailableAccurate and reliable interpolation of groundwater
depth over a region is a pre-requisite for efficient
planning and management of water resources. The performance
of two deterministic, such as inverse distance
weighting (IDW) and radial basis function (RBF) and two
stochastic, i.e., ordinary kriging (OK) and universal kriging
(UK) interpolation methods was compared to predict spatio-
temporal variation of groundwater depth. Pre- and postmonsoon
groundwater level data for the year 2006 from
110 different locations over Delhi were used. Analyses
revealed that OK and UK methods outperformed the IDW
method, and UK performed better than OK. RBF also
performed better than IDW and OK. IDW and RBF
methods slightly underestimated and both the kriging
methods slightly overestimated the prediction of water
table depth. OK, RBF and UK yielded 27.52, 27.66 and
51.11 % lower RMSE, 27.49, 35.34 and 51.28 % lower
MRE, and 14.21, 16.12 and 21.36 % higher R2 over IDW.
The isodepth-area curves indicated the possibility of
exploitation of groundwater up to a depth of 20 m.Not Availabl
Retinal Blood Vessel Extraction from Fundus Images Using Enhancement Filtering and Clustering
Screening of vision troubling eye diseases by segmenting fundus images eases the danger of loss of sight of people. Computer assisted analysis can play an important role in the forthcoming health care system universally. Therefore, this paper presents a clustering based method for extraction of retinal vasculature from ophthalmoscope images. The method starts with image enhancement by contrast limited adaptive histogram equalization (CLAHE) from which feature extraction is accomplished using Gabor filter followed by enhancement of extracted features with Hessian based enhancement filters. It then extracts the vessels using K-mean clustering technique. Finally, the method ends with the application of a morphological cleaning operation to get the ultimate vessel segmented image. The performance of the proposed method is evaluated by taking two different publicly available Digital retinal images for vessel extraction (DRIVE) and Child heart and health study in England (CHASE_DB1) databases using nine different performance matrices. It gives average accuracies of 0.952 and 0.951 for DRIVE and CHASE_DB1 databases, respectively
Not Available
Not AvailableAccurate and reliable interpolation of groundwater
depth over a region is a pre-requisite for efficient
planning and management of water resources. The performance
of two deterministic, such as inverse distance
weighting (IDW) and radial basis function (RBF) and two
stochastic, i.e., ordinary kriging (OK) and universal kriging
(UK) interpolation methods was compared to predict spatio-
temporal variation of groundwater depth. Pre- and postmonsoon
groundwater level data for the year 2006 from
110 different locations over Delhi were used. Analyses
revealed that OK and UK methods outperformed the IDW
method, and UK performed better than OK. RBF also
performed better than IDW and OK. IDW and RBF
methods slightly underestimated and both the kriging
methods slightly overestimated the prediction of water
table depth. OK, RBF and UK yielded 27.52, 27.66 and
51.11 % lower RMSE, 27.49, 35.34 and 51.28 % lower
MRE, and 14.21, 16.12 and 21.36 % higher R2 over IDW.
The isodepth-area curves indicated the possibility of
exploitation of groundwater up to a depth of 20 m.Not Availabl
Not Available
Not AvailableAccurate and reliable interpolation of groundwater
depth over a region is a pre-requisite for efficient
planning and management of water resources. The performance
of two deterministic, such as inverse distance
weighting (IDW) and radial basis function (RBF) and two
stochastic, i.e., ordinary kriging (OK) and universal kriging
(UK) interpolation methods was compared to predict spatio-temporal
variation of groundwater depth. Pre- and postmonsoon
groundwater level data for the year 2006 from
110 different locations over Delhi were used. Analyses
revealed that OK and UK methods outperformed the IDW
method, and UK performed better than OK. RBF also
performed better than IDW and OK. IDW and RBF
methods slightly underestimated and both the kriging
methods slightly overestimated the prediction of water
table depth. OK, RBF and UK yielded 27.52, 27.66 and
51.11 % lower RMSE, 27.49, 35.34 and 51.28 % lower
MRE, and 14.21, 16.12 and 21.36 % higher R2 over IDW.
The isodepth-area curves indicated the possibility of
exploitation of groundwater up to a depth of 20 m.Not Availabl