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...

A novel adaptive video object tracking algorithm is proposed using intensity based and feature based techniques which results in improved reliability and at the same time it aims to reduce computational complexity. This is achieved by intelligently combining SIFT and BMA and making it adaptive to the speed of the moving object. Tracking frame by frame using SIFT which is successful for detectin...

Success of scale-invariant feature transform (SIFT) image registration is limited when attempted on camera footage taken under water. This is, largely due to the poor image quality inherent to imaging in aquatic environments. In this research we aim to overcome this shortcoming using a new method of pre-processing of true-color imagery taken under water based on the Contrast Limited Adaptive Hi...

Materials genome initiatives sift big data.

Over the last decade, there have been renewed efforts into wine grape breeding within research community. Quick characterisation by phenotyping of quality traits, including aroma composition, remains challenging. Selected Ion Flow Tube Mass Spectrometry (SIFT-MS), a high throughput soft ionisation technology first available in 2008, could be particularly useful for this purpose. In light this, ...