Purwarupa Sistem Penggabungan Foto Udara Pada UAV Menggunakan Algoritma Surf (Speeded-Up Robust Features)
Farida Dewanti(1*), Raden Sumiharto(2)
(1) 
(2) Department of Computer Science and Electronics, Universitas Gadjah Mada
(*) Corresponding Author
Abstract
This system is designed to be able to merge aerial images by using SURF algorithm, Flann, RANSAC, and warpPerspective. SURF algorithm is used as a keypoint detector from each of the input images. Flann method to perform keypoint matching is found. RANSAC homography matrix used for the search. WarpPerspective method used for merging the two inputs that have a match keypoint.
The test consists of several types of variations such as the intersection of the minimal variation, variation in scale and rotation variations. Variation that produces intersection minimum value of 15% and a minimum number of keypoint accords between the two images can be combined is 5. Variation of rotation to any angle difference between the two images can still be combined. Minimum scale variations which can be combined image is the image scale is reduced to 75% of the size of the original image, and the image scale is enlarged to 600% of its original size to a maximum variation of magnification scale.
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[1] Li. Chaokui, Yang. Gang, Wu. Jun and Wang. Fang, 2012. The UAV Video Image Stitching Based on Improved Moravec Corner Matching Method. China
[2] Bay, H., Tuytelaars,T. & Van Gool, L. (2006) SURF: Speeded Up Robust Features. Proceedings of the ninth European Conference on Computer Vision
[3] Tania, Ken, 2010. Tattoo recognition Based On Speed Up with Robust Feature (SURF). Risalah Lokakarya Komputasi dalam Sains dan Teknologi Nuklir.
[4] Darajati, Aisah. 2012. Implementasi Dan Analisis Citra Mosaik Berbasis Fitur Dengan Metode Global Alignment Untuk Pembentukan Citra Panorama Pada Android.Fakultas Elektro dan Komunikasi Universitas Telkom. Bandung
DOI: https://doi.org/10.22146/ijeis.7640
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