Sasirangan Motifs Classification using Scale- Invariant Feature Transform (SIFT) and Support Vector Machine (SVM) [PDF]
MATEC Web of Conferences, 2019 Sasirangan is one of the traditional cloth from Indonesia. Specifically, it comes from South Borneo. It has many variations of motifs with a different meaning for each pattern.
Alkaff Muhammad +3 more
doaj +7 more sources
Possibility Study of Scale Invariant Feature Transform (SIFT) Algorithm Application to Spine Magnetic Resonance Imaging. [PDF]
PLoS ONE, 2016 The purpose of this study is an application of scale invariant feature transform (SIFT) algorithm to stitch the cervical-thoracic-lumbar (C-T-L) spine magnetic resonance (MR) images to provide a view of the entire spine in a single image.
Dong-Hoon Lee, Do-Wan Lee, Bong-Soo Han
doaj +8 more sources
N-SIFT: N-DIMENSIONAL SCALE INVARIANT FEATURE TRANSFORM FOR MATCHING MEDICAL IMAGES [PDF]
IEEE Transactions on Image Processing, 2007 We propose the n-dimensional scale invariant feature transform (n-SIFT) method for extracting and matching salient features from scalar images of arbitrary dimensionality, and compare this method's performance to other related features. The proposed features extend the concepts used for 2-D scalar images in the computer vision SIFT technique for ...
Warren Cheung, Ghassan Hamarneh
semanticscholar +8 more sources
Pengenalan Barang Pada Kereta Belanja Menggunakan Metode Scale Invariant Feature Transform (SIFT) [PDF]
Jurnal Teknologi Informasi dan Ilmu Komputer, 2018 Menunggu dalam suatu antrian di supermarket sering terjadi dalam kehidupan sehari-hari. Antrian tersebut terjadi karena pada kasir mengharuskan setiap barang diperiksa untuk dipindai menggunakan barcode. Hal ini dapat diatasi dengan menggunakan aplikasi
Ronny Makhfuddin Akbar, Nani Sunarmi
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Fuzzy match index for scale‐invariant feature transform (SIFT) features with application to face recognition with weak supervision [PDF]
IET Image Processing, 2015 A fuzzy match index for scale‐invariant feature transform (SIFT) features is proposed in this study that cumulatively involves all the test SIFT keypoints in the decision‐making process. The new fuzzy SIFT classifier is adapted successfully for robust face recognition from complex backgrounds without using any face cropping tools and using only a ...
Seba Susan +4 more
semanticscholar +4 more sources
Hexagonal scale invariant feature transform (H-SIFT) for facial feature extraction
Journal of Applied Research and Technology, 2015 AbstractFeature transformation and key-point identifi is the solution to many local feature descriptors. One among such descriptor is the Scale Invariant Feature Transform (SIFT). A small effort has been made for designing a hexagonal sampled SIFT feature descriptor with its applicability in face recognition tasks. Instead of using SIFT on square image
Aisha Azeem +3 more
semanticscholar +5 more sources
Local-Peak Scale-Invariant Feature Transform for Fast and Random Image Stitching [PDF]
SensorsImage stitching aims to construct a wide field of view with high spatial resolution, which cannot be achieved in a single exposure. Typically, conventional image stitching techniques, other than deep learning, require complex computation and are thus ...
Hao Li +3 more
doaj +4 more sources
Scale Invariant Feature Transform for n-Dimensional Images (n-SIFT)
The Insight Journal, 2007 This document describes the implementation of several features previously developed[2], extending the 2D scale invariant feature transform (SIFT)[4, 5] for images of arbitrary dimensionality, such as 3D medical image volumes and time series, using ITK1.
Warren Cheung, Ghassan Hamarneh
semanticscholar +3 more sources
Currency recognition using a smartphone: Comparison between color SIFT and gray scale SIFT algorithms [PDF]
Journal of King Saud University: Computer and Information Sciences, 2017 Banknote recognition means classifying the currency (coin and paper) to the correct class. In this paper, we developed a dataset for Jordanian currency.
Iyad Abu Doush, Sahar AL-Btoush
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pi-SIFT: A Photometric and Scale Invariant Feature Transform [PDF]
2008 19th International Conference on Pattern Recognition, 2010 In this chapter, we presented a novel photometric quasi-invariant SIFT descriptor, PHI-SIFT, which is insensitive to photometric variations in addition to geometric invariance. The dichromatic reflection model is used for extracting photometric quasi-invariant features and the similar approach to the SIFT is used for obtaining geometric invariance. For
Jae‐Han Park +3 more
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