The scanning electron microscope (SEM), as one of the most commonly used instruments in
biology and material sciences, employs electrons instead of light to determine the surface …

This paper introduces a high-speed all-hardware scale-invariant feature transform (SIFT)
architecture with parallel and pipeline technology for real-time extraction of image features …

This paper proposes a parallel hardware architecture for real-time image classification
based on scale-invariant feature transform (SIFT), bag of features (BoFs), and support vector …

Detecting and matching image features is a fundamental task in video analytics and
computer vision systems. It establishes the correspondences between two images taken at …

Although some researchers have proposed the Field Programmable Gate Array (FPGA)
architectures of Feature From Accelerated Segment Test (FAST) and Binary Robust …

Image feature extraction constitutes a fundamental task in robotic vision applications. Scale-
Invariant Feature Transform (SIFT) has been widely used as a robust method for detecting …

Image feature detection is a key task in computer vision. Scale Invariant Feature Transform
(SIFT) is a prevalent and well known algorithm for robust feature detection. However, it is …

This paper proposes a novel hardware design method of scale-invariant feature transform
(SIFT) algorithm for implementation on field-programmable gate array (FPGA). To reduce the …

A parallel hardware architecture for real-time image feature detection based on the SIFT
(Scale Invariant Feature Transform) algorithm has been presented. The proposed parallel …

A recent trend in several robotics tasks is to consider vision as the primary sense to perceive
the environment or to interact with humans. Therefore, vision processing becomes a central …