Results 261 to 270 of about 198,198 (336)

Secure outsourcing SIFT: Efficient and Privacy-Preserving Image Feature Extraction in the Encrypted Domain

IEEE Transactions on Dependable and Secure Computing, 2020
Multimedia data needs huge storage space, and application of multimedia data needs powerful capability of computing. Cloud computing can help owner of multimedia data to deal with it.
Linzhi Jiang, Chunxiang Xu, Xiaofang Wang, Bo Luo, Huaqun Wang   +4 more
semanticscholar   +1 more source

Integrating SIFT and CNN Feature Matching for Partial-Duplicate Image Detection

IEEE Transactions on Emerging Topics in Computational Intelligence, 2020
With the increasing popularity of various deep neural networks in the area of computational intelligence, the research attention for content-based image detection/retrieval has been shifted from the handcrafted local features such as scale invariant ...
Zhili Zhou, Q. M. J. Wu, Shaohua Wan, Wendi Sun, Xingming Sun   +4 more
semanticscholar   +1 more source

Comparison of Feature Detection and Matching Approaches: SIFT and SURF

Global Research and Development Journals
Feature detection and matching are used in image registration, object tracking, object retrieval etc. There are number of approaches used to detect and matching of features as SIFT (Scale Invariant Feature Transform), SURF (Speeded up Robust Feature ...
D. Mistry, A. Banerjee
semanticscholar   +1 more source

Ghost-free multi exposure image fusion technique using dense SIFT descriptor and guided filter

Journal of Visual Communication and Image Representation, 2019
A ghost-free multi-exposure image fusion technique using the dense SIFT descriptor and the guided filter is proposed in this paper. The results suggest that the presented scheme produces high-quality images using ordinary cameras and that too without the
Naila Hayat, M. Imran
semanticscholar   +1 more source

HALF-SIFT: High-Accurate Localized Features for SIFT

2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, 2009
In this paper, the accuracy of feature points in images detected by the scale invariant feature transform (SIFT) is analyzed. It is shown that there is a systematic error in the feature point localization. The systematic error is caused by the improper subpel and subscale estimation, an interpolation with a parabolic function.
Kai Cordes, Oliver Müller 0003, Bodo Rosenhahn, Jörn Ostermann   +3 more
openaire   +1 more source

Combination of SIFT and Canny Edge Detection for Registration Between SAR and Optical Images

IEEE Geoscience and Remote Sensing Letters, 2020
Scale-invariant feature transform (SIFT) has been successfully used for optical image registration, but it cannot produce satisfying results when directly applied to synthetic aperture radar (SAR) images.
Wannan Zhang
semanticscholar   +1 more source

AH-SIFT: Augmented Histogram based SIFT descriptor

2012 19th IEEE International Conference on Image Processing, 2012
We propose Augmented Histogram (AH), a conceptually novel and systematic approach to enhancing the representational power of histogram-based local image descriptors such as SIFT. Our method takes a simple form that augments the histogram of local image patch features with a set of circular means and variances.
Hao Tang 0001, Feng Tang
openaire   +1 more source

TOP-SIFT: A New Method for SIFT Descriptor Selection

2015 IEEE International Conference on Multimedia Big Data, 2015
The large amount of SIFT descriptors in an image and the high dimensionality of SIFT descriptor has made problems for large-scale image dataset in terms of speed and scalability. In this paper, we propose a descriptor selection algorithm via dictionary learning and only a small set of features are reserved, which we refer to as TOP-SIFT.
Yujie Liu 0002, Xiaoming Chen, Qilu Zhao, Zongmin Li, Jianping Fan 0001   +4 more
openaire   +1 more source

Understanding gas phase ion chemistry is the key to reliable SIFT-MS analyses.

Analytical Chemistry, 2020
Ion-molecule reactions (IMR) are at the very core of trace gas analyses in modern chemical ionisation (CI) mass spectrometer instruments, which are increasingly being used in diverse areas of research and industry. The focus of this Perspective is on the
David R. Smith, M. McEwan, P. Španěl
semanticscholar   +1 more source

MI-SIFT

Proceedings of the ACM International Conference on Image and Video Retrieval, 2010
The best known Scale-Invariant Feature Transform (SIFT) shows its superior performance in a variety of image processing tasks due to its distinctiveness, invariance to scale, rotation and local geometric distortion. Despite its remarkable performance, SIFT is not invariant to mirror images and grayscale-inverted images.This paper proposes an improved ...
Rui Ma, Jian Chen, Zhong Su
openaire   +1 more source