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An Image Matching Method Based on SIFT Feature
Applied Mechanics and Materials, 2012Aiming at problems about repeat matching and wrong matching appeared when traditional SIFT algorithm was used in image matching, an image matching method based on SIFT feature was put forward. Firstly, SIFT features were extracted by traditional SIFT algorithm and candidate matching point pairs were obtained by the nearest neighbor rule.
Zhao Ming Shi +3 more
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SIFT based geometric distortion correction method
2008 23rd International Symposium on Computer and Information Sciences, 2008It is very important to cope with geometric distortions especially for robust watermarking systems since these attacks break the synchronization between the watermark and detector. In general, robustness to geometric attacks is considered as a different concept as rotation, scale and translation (RST) invariant watermarking.
Erkan Yavuz, Ziya Telatar
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Normalization Methods of SIFT Vector for Object Recognition
2011 10th International Symposium on Distributed Computing and Applications to Business, Engineering and Science, 2011In the clustering of key points, the ratio of inter-class distance and intra-class distance is enlarged using Normalized SIFT vectors. In order to significantly make the ratio larger, a new normalization method is proposed, which is termed the i®normalization method based on seedpoints'. In image preprocessing, for the removal of the object background,
Hongxia Wang +3 more
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A Method of SIFT Simplifying and Matching Algorithm Improvement
2016 International Conference on Industrial Informatics - Computing Technology, Intelligent Technology, Industrial Information Integration (ICIICII), 2016Scale-invariant feature transform (SIFT) is a popular pattern recognition method in 2D-image because it can abstracts the features which are invariant to rotation, scale zooming, brightness changing. So it demonstrates a certain stability to objects subjected to view point changing and noise distribution.
Xinmin Zhou, Kaiyuan Wang, Jian Fu
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An Improved Image Registration Method Based on SIFT
2009 International Asia Symposium on Intelligent Interaction and Affective Computing, 2009The features of SIFT are widely used in image matching because of it’s invariantion to images scale and rotation, but 128-dimensional description of the feature point reduce the efficiency of the algorithm. This paper presents an improved algorithm of SIFT, using ring and sequence of each feature vector to ensure rotation invariance while reducing the ...
Zhenjie Hou +4 more
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OBJECT RECOGNITION WITH SIFT AND MI-SIFT METHODS
2015This study, which has been commonly used in object recognition area for 10 years, is based on the recognition of special point-based objects and there are differences in some areas such as luminance, anguler and resistance from cyclic and dimensional changes.
HARDALAÇ, Fırat +3 more
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Psychological Type and Liturgical Preaching: The Sift Method
Liturgy, 2006(2006). Psychological Type and Liturgical Preaching: The Sift Method. Liturgy: Vol. 21, No. 3, pp. 11-20.
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The Application of SIFT Method towards Image Registration
Advanced Materials Research, 2014The scale invariant features transform (SIFT) is commonly used in object recognition,According to the problems of large memory consumption and low computation speed in SIFT (Scale Invariant Feature Transform) algorithm.During the image registration methods based on point features,SIFT point feature is invariant to image scale and rotation, and provides
Shu Guang Wu, Shu He, Xia Yang
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A copy-move forgery detection method based on CMFD-SIFT
Multimedia Tools and Applications, 2017A very common way of image tampering is the copy-move attack. When creating a copy-move forgery, it is often necessary to add or remove important objects from an image. To carry out forensic analysis of such images, various copy-move forgery detection (CMFD) methods have been developed in the literatures.
Bin Yang 0025 +4 more
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A SIFT-point distribution-based method for head pose estimation
2012 IEEE International Workshop on Machine Learning for Signal Processing, 2012Estimating the head pose of a person in a video or image sequence is a challenging problem in computer vision. In this paper, we present a new technique on how to estimate the human face pose from a video sequence, by creating a probabilistic model based on the scale invariant features of the face. This method consists of four major steps: (1) the face
Nastaran Ghadarghadar +3 more
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