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Edge
detection is an image processing

Technique for finding the boundaries of
objects within images. And it is based on the discontinuous in brightness. Most
commonly edge detection is used for image segmentation and data extraction in
area such as computer vision, machine vision, image processing the result and
output are in the form of binary. The edge detection is processed on the
preprocessed image the resulting image in the form of binary. Consider an iris
edge detection it provides a map of eyelid

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Edge
candidates from this we can improve the speed and robustness of the algorithm
and the computational steps are very simple. In this method only the edges
playing a vital role we do not concentrate on the whole image. If the edge
detection step is ignored in this process the output of the image which consist
of so many errors because of the eyelid, pupil and the connections between the
eyelids/iris and iris/sclera boundaries.

The different types of the edge
detection makes to recognize the iris feature. In this paper I have used four
different types of the edge detection method that is canny, sobal, prewitt and
Roberts. And it is clear that the obtained results of the prewitt, sobal,
Roberts are approximately similar, but the results of a leads to give different
details, this is due to high power of canny mask. And the edge detection only
calculates the local maxima of the gradient of I.

 

7.1 canny edge detection:

The
most common method of using the edge detection is canny edge detection in image
processing. The canny edge detection is finds only the maximum level of image
of the gradient I. where the gradient of the I is represented by the Gaussian
filter and it has two threshold points to detect the strong and weak edges. The
canny edge detection algorithm runs on 5 steps which explains below

1.
Smoothing

2.
Finding gradient

3. Non-maximum suppression

4. Double thresholding

5. Edge tracking by hysteresis

The
canny edge detection is used to find the wide range of the edges by using this
algorithms. Canny edge detection is a techniques to extract the useful
structural information from the different types of the objects and dramatically
reduce the amount of data. And it has the low error rate and the detection
should be accurate.

Canny edge detection

Sobal edge detection

Prewitt edge detection

Roberts edge detection

 

8. CONCLUSION:

Biometrics
recognition is an automatic recognition of an individual based on the
behavioral and physiological features. Iris recognition have been proven to be
very effective and secured and the information’s are protected very well. And
there is hacking and mal activities in this iris recognition security systems
so in modern days the iris recognition is used most of the application. In this
paper the biometric iris recognition system is implemented via the hybrid
techniques such as wavelet and the feature extraction and the edge detection
techniques. This approach leads the high level and precisionized security
protection other than the biometric recognition system.

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