DETECTION OF BLOOD VESSELS IN RETINA TO DIAGNOSE RETINOPATHY FROM RGB RETINA MODEL. GOBAR FILTER WITH LOCAL ENTROPY THERSHOULDING FOR VESSELS SEGMENTATION UNDER VARIOUS NORMAL OR ABNORMAL CONDITIONS.

1. By
SATHISHKLUMAR G
(sathishsak111@gmail.com)
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2.  Abstract
 Block Diagram
 Pre Processing
 Gabor Filter
 Local Entropy Thresholding
 Advantages
 Conclusion
 Reference
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3.  Detection of Blood Vessels in Retina to diagnose Diabetic
Retinopathy from RGB Retina model.
 It is complicated due to presence of bright and Dark tissues in
Retinal images.
 Gabor Filter with local entropy thresholding for vessels
segmentation under various normal or abnormal conditions.
 Method can be applied for image registration purpouse to
monitor Diabetic Retinopathy.
 The performance of the proposed algorithm is evaluated by
MATLAB
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4. .
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RGB Retina
Model
PreProcessing
Adaptive
Histogram
Equalization
Optimized Gabor
Filter
Local Entropy
Thresholding
Binary Image
of Blood
Vessels

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6.  .
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(a) Red Channel Extraction
(b) Green Channel Extraction
(c) Blue Channel Extraction

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9.  Obtain all the inputs
 Pre process the inputs
 Process each contextual region thus
producing grey level mapings
 Interpolate grey level mappings in
order to assemble final clache image
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11.  The Gabor Filter introduced by Dennis Gabor
 Linear filter used for texture analysis
 Frequencies content in image in specific direction
in localised region around the point
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14. Thresholding an image that
selects an optimum
threshold value
By choosing pixel intensity
from image's histogram
That exhibit maximum
entropy over the entire
image.
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15.  Low Noise
 High Accuracy
 Better visual Quality’
 Low Probabiity of Error
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16. Analysis manifests maximum true positive rate and
reduces false vessels detection in the fundus.
This is accessed by Drive database images .
Method can be applied for image registration
purpouse to monitor Diabetic Retinopathy
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