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Title |
IRIS Image Edge Detection using Wavelets |
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Author |
Dr.A.SENTHIL ARUMUGAM, J.JESLIN SUJI, Dr.D.KIRUBA JOTHI |
| Citation |
Vol. 25 No. 12 pp. 81-86 |
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Abstract |
Edge detection is a terminology in image processing and computer vision, particularly in the areas of feature detection and feature extraction, to refer to algorithms which aim at identifying points in a digital image at which the image brightness changes sharply or more formally has discontinuities. There are many ways to perform edge detection. However, the most may be grouped into two categories, gradient and Laplacian. The gradient method detects the edges by looking for the maximum and minimum in the first derivative of the image. The Laplacian method searches for zerocrossings in the second derivative of the image to find edges. Another method of detecting edges is using wavelets. Specifically a two-dimensional Haar wavelet transform of the image produces essentially edge maps of the vertical, horizontal, and diagonal edges in an image. Wavelet analysis is a local analysis; it is especially suitable for time frequency analysis, which is essential for singularity detection. This research focuses on Haar and Daubechies D4 wavelet transform to find an edge from an image. The proposed technique has been demonstrated for iris imagery and the reported results have been compared with Daubechies D4 wavelet based edge detection technique. |
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Keywords |
Haar,Wavelets,Edge Detection, IRIS Image Edge |
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