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Implementation of Efficient Algorithm for Exact Hausdorff Distance


Trupti Nagesh Wardole , JSPM's BSIOTR, Wagholi Pune 412207; Prof. S. A. Patil, JSPM's BSIOTR, Wagholi Pune 412207; Snehal Kundlik Zarekar, JSPM's BSIOTR, Wagholi Pune 412207; Ashwini Walmik Waghole, JSPM's BSIOTR, Wagholi Pune 412207


Hausdorff Distance, Early Breaking, Random Sampling in Place of Scanning, Excluding Intersection, Runtime Analysis


The Hausdorff distance is very important source in computer field. It is the very important source for the various image processing applications including image tonning stirringthe image, acknowledgement and track, shape recovery.However,there is no efficient algorithm has been report that compute the correct Hausdorff distance in the linear time for the compare two images. There are less number of methods that have been planned to compare the exact Hausdorff distance with higher estimate error. In this paper, we proposed a linear time algorithm for comparing the exact Hausdorff distance with less estimate error. The proposed method is helpful to decrese the time taken for processing, while minimizie the fault rate in content-based image processing and the examinaton. The Hausdorff distance is the evaluate of difference between two sets which is widely used in the variety of the applications. This has applicatios, for the example, in the image processing. In this paper we propose a novel efficient algorithm for comparing the approximate Hausdorff distance. The proposed algorithm is experienced against the HD algorithm of the generally used National Library of Medicine Insight Segmentation and Registration Toolkit (ITK) using the magnetic resonance volumes with the extremely large size. The proposed algorithm outperforms the ITK HD algorithm both in the rate and the memory essential. The Hausdorff Distance differ from number of other shape relationship methods in that no connections between the model and the image is resulting. The method is relatively broadminded of the less position faults such as those that happen with edge detectors and the other feature removal methods.

Other Details

Paper ID: IJSRDV4I20942
Published in: Volume : 4, Issue : 2
Publication Date: 01/05/2016
Page(s): 821-825

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