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Survey of Feature Points Detection and Matching using SURF, SIFT and PCA-SIFT

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This paper summarizes the three robust feature detection and matching methods: Scale Invariant Feature Transform (SIFT), Principal Component Analysis (PCA)–SIFT and Speeded Up Robust Features (SURF). SIFT find its interest points using Difference of Gaussian (DoG). SIFT presents its stability in most situations although it’s slow. PCA-SIFT show its advantages in rotation and illumination change and it is faster than SIFT.SURF is the fastest one with good performance as the same as SIFT. ‘Fast-Hessian’ detector that used in SURF is more than 3 times faster that DOG.

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Scale Invariant Feature Transform (SIFT), Principal Component Analysis (PCA)-SIFT, Speeded Up Robust Feature (SURF).

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"Survey of Feature Points Detection and Matching using SURF, SIFT and PCA-SIFT", International Journal of Emerging Technologies and Innovative Research ( | UGC and issn Approved), ISSN:2349-5162, Vol.1, Issue 1, page no. pp35-41, June-2014, Available at : &

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Published Paper ID: JETIR1401007
Registration ID: 140022
Published In: Volume 1 | Issue 1 | Year June-2014
DOI (Digital Object Identifier):
Page No: 35-41
ISSN Number: 2349-5162

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(Volume 5 | Issue 1 | January 2018 |Impact factor 5.87)

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