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S KOM 0905653 Bibliography

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In this paper, multi-feature fusion using Scale Invariant Feature Transform (SIFT) and Local Extensive Binary Pattern (LEBP) was proposed to obtain a feature that

Several object detection algorithms have been compared such as Scale Invariant Feature Transform (SIFT), Speeded-Up Feature Transform (SuRF), Center Surrounded External

Pada penelitian ini dibuat sistem pengenalan barang pada kereta belanja menggunakan metode Scale Invariant Feature Transform (SIFT) yang dirancang agar dapat

Tujuan dari penelitian ini adalah untuk menganalisa mengkomparasi Algoritma Scale Invariant Feature Transform (SIFT) dengan Algoritma K-Nearest Neighbor (K-NN) untuk

(Lowe, 2004) presented a method for extracting distinctive invariant features Scale-invariant feature transform (SIFT) key points which is used in building detection. L., Boye

Dalam penelitian ini digunakan teknik Scale Invariant Transform Feature (SIFT) dan Phase Colleration Only (POC) sebagai fitur ekstraksi yang dapat mengatasi masalah

Then, FiSP is paired with Harris corner, scale-invariant feature transform SIFT, speeded-up robust feature SURF, Ghassabi's and D-Saddle feature point extraction methods to assess its

Keywords: Harris corner detector, RANSAC Random Sample Consensus, SIFT Scale Invariant Feature Transform, SURF Speeded up Robust Features, I INTRODUCTION Image mosaicing is an