The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translationand rotation-invariant local features in images. The original SIFT algorithm has been successfully applied in general object detection and recognition tasks, panorama stitching and others. One of its more recent uses also includes face recognition, where it was shown to deliver encouragin...

In recent years the environmental and human health impacts of volatile organic compounds (VOCs) have become more apparent, resulting in increased analysis demand. The gold-standard chromatographic techniques continue to be employed for most laboratory analyses. However, they made only modest gains productivity over years, these are primarily due automated sample preparation injection. Alternati...

This paper introduces a framework for relational schema navigation via a Web-based browser application that uses Formal Concept Analysis as the metaphor for analysis and interaction. Formal Concept Analysis is a rich framework for data analysis based on applied lattice and order theory. The application we develop, D-SIFT, is intended to provide users untrained in Formal Concept Analysis with pr...

Detection and description of local features are a classical problem in image processing and multimedia content analysis. Based on the inhomogeneity of visual orientation in human visual system, we propose a novel algorithm S-SIFT to detect and describe local image features. In three stages of SSIFT, the information from the least discriminability orientation is omitting. Compared with the stand...

In this paper we describe an FPGA implementation of the Scale Invariant Feature Transform (SIFT) algorithm. The is required as its a lightweight device which makes it ideal for vision-guided hybrid neuro-prostheses utilised upper limbs replacement. SIFT point detection needed computation coordinates object-to-grasp in wearable multi-camera system. A modified algorithm proposed and into C/C++ la...

Abstract An approach is proposed for recovering affine correspondences (ACs) from orientation- and scale-covariant, e.g., SIFT, features exploiting pre-estimated epipolar geometry. The method calculates the parameters consistent with geometry point coordinates scales rotations which feature detector obtains. closed-form solver returns a single solution extremely fast, i.e., 0.5 $$\upmu $$ <mml:...

The paper reports about investigations into the utilization of the SIFT algorithm to support image matching between different image domains. The Scale-Invariant Feature Transformation, proposed by Lowe in 1999, is a highly robust technique that has been widely used in the computer vision community. Though, SIFT is known in mapping circles, so far its use is rather limited. The objective of our ...

Signature recognition is the process of verifying a writer’s identity by checking the signature against samples previously stored in the database. Several techniques such as the distance-based and statistical classifiers used for feature extraction on a signature image are not invariant to scaling and rotation and the Scale invariant feature transform (SIFT) though invariant to scaling and rota...

SIFT features are distinctive invariant features used to robustly describe and match digital image content between different views of a scene. While invariant to scale and rotation, and robust to other image transforms, the SIFT feature description of an image is typically large and slow to compute. This paper presents a method to reduce the size, complexity and matching time of SIFT feature se...