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Abstract
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Article Information:
Blood Vessel Segmentation for Retinal Images Based on Am-fm Method
S. Dhanalakshmi and T. Ravichandran
Corresponding Author: S. Dhanalakshmi
Submitted: March 23, 2012
Accepted: April 30, 2012
Published: December 15, 2012 |
Abstract:
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This system proposes a new supervised approach for the blood vessel segmentation method in retina
image. This proposed system overcomes the problem of segmenting thin vessels. This method uses a Fuzzy
Neural Network (FNN) scheme for pixel classification and computes a 7-D vector composed of gray-level,
moment invariants-based features for pixel representation and AM-FM method for composition of the images.
The method was evaluated on the publicly available DRIVE and STARE databases, widely used for this
purpose, since they contain retinal images where the vascular structure has been precisely marked by experts.
Method performance on both sets of test images is better than other existing solutions in literature. The method
proves especially accurate for vessel detection in STARE images. Its effectiveness and robustness with different
image conditions together with its simplicity and fast implementation make this blood vessel segmentation
proposal suitable for retinal image computer analyses such as automated screening for early diabetic retinopathy
detection.
Key words: Diabetic retinopathy, moment invariants, retinal imaging, vessels segmentation, , ,
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Abstract
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Cite this Reference:
S. Dhanalakshmi and T. Ravichandran, . Blood Vessel Segmentation for Retinal Images Based on Am-fm Method. Research Journal of Applied Sciences, Engineering and Technology, (24): 5519-5524.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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