a r t i c l e i n f o Extracting local keypoints and keypoint descriptions from images is a primary step for many computer vision and image retrieval applications. In the literature, many researchers have proposed methods for representing local texture around keypoints with varying levels of robustness to photometric and geometric transformations. Gradient-based descriptors such as the Scale In...

Copy-Move Forgery (CMF) is a simple and effective operation to generate forged digital images. Recent, techniques on Scale Invariant Features Transform (SIFT) are commonly used to detect CMF. Various approaches under the SIFTframework are the most acceptable ways to CMF detection due to the robust performance of SIFT. However, for some CMF images, these approaches cannot produce satisfactory de...

The SIFT algorithm (Scale Invariant Feature Transform) proposed by Lowe [1] is an approach for extracting distinctive invariant features from images. It has been successfully applied to a variety of computer vision problems based on feature matching including object recognition, pose estimation, image retrieval and many others. However, in real-world applications there is still a need for impro...

PURPOSE In this paper, the authors proposed a new 3D registration algorithm, 3D-scale invariant feature transform (SIFT)-Flow, for multiatlas-based liver segmentation in computed tomography (CT) images. METHODS In the registration work, the authors developed a new registration method that takes advantage of dense correspondence using the informative and robust SIFT feature. The authors comput...

The past ten years have seen the discovery of a number of “power laws” in networking. When applied to network trafic, these laws imply the following 80-20 rule: 80% of the work is brought by 20% of the flows; in particular, 80% of Internet packets are generated by 20% of the flows. Heavy advantage could be taken of such a statistic if we could identify the packets of these dominant flows with m...

Methods for automated prediction of deleterious protein mutations have utilized both structural and evolutionary information but the relative contribution of these two factors remains unclear. To address this, we have used a variety of structural and evolutionary features to create simple deleterious mutation models that have been tested on both experimental mutagenesis and human allele data. W...

Scale-Invariant Feature Transform (SIFT) is being investigated more and more to realize a less-constrained hand vein recognition system. Contrast enhancement (CE), compensating for deficient dynamic range aspects, is a must for SIFT based framework to improve the performance. However, evidence of negative influence on SIFT matching brought by CE is analysed by our experiments. We bring evidence...

The objective of this work is to provide an experimental numerical technique that combines the use of computer vision through the SIFT technique (Scale Invariant Features Transform) with a meshless numeric method to determine displacement and strain fields on the surface of a deformable material. The experimental part of this technique is based on the capture of images during the deformation pr...

Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we propose using the combination of Affine Scale Invariant Feature Transform (SIFT) and Probabilistic Similarity for face recognition under a large viewpoint change. Affine ...