In the photogrammetry field, interest in region detectors, which are widely used in Computer Vision, is quickly increasing due to the availability of new techniques. Images acquired by Mobile Mapping Technology, Oblique Photogrammetric Cameras or Unmanned Aerial Vehicles do not observe normal acquisition conditions. Feature extraction and matching techniques, which are traditionally used in pho...

According to the rotational invariance of Harris corner detector and the robustness of Sift descriptor. An improved Harris-Sift corner descriptor was proposed. At first, the algorithm given multi-scale strategy to Harris corner, improved corner counting method and removed redundant points at the same time, then, the corner was directly applied to low-pass Gaussian filter image. Based on the his...

Scale Invariant Feature Transform (SIFT) algorithm is a widely used computer vision algorithm that detects and extracts local feature descriptors from images. SIFT is computationally intensive, making it infeasible for single threaded implementation to extract local feature descriptors for high-resolution images in real time. In this paper, an approach to parallelization of the SIFT algorithm i...

In machine vision, Scale-invariant feature transform (SIFT) and its variants have been widely used in image classification task. However, the high dimensionality nature of SIFT features, usually in the order of multiple thousands per image, would require careful consideration in place to achieve accurate and timely categorization of objects within images. This paper explores the possibility of ...

SIFT Feature with Relevance Feedback for Image Retrieval Written by Administrator Wednesday, 16 March 2011 08:52 Last Updated Monday, 21 March 2011 07:32 In this paper, we used the Scale Invariant Feature Transform (SIFT) feature for image retrieval. SIFT descriptors are invariant to image scaling, transformation,rotation and partially invariant to illumination changes and affine, gives the loc...

SIFT is a novel and promising method for iris recognition. However, some shortages exist in many related methods, such as difficulty of feature extraction, feature loss, and noise point introduction. In this paper, a new method named SIFT-based iris recognition with normalization and enhancement is proposed for achieving better performance. In Comparison with other SIFT-based iris recognition a...

Recent years have encountered a massive growth in social networking due to which immense numbers of videos are being shared on video sharing sites but issue of copyright infringement arises with uploading of illicit or transformed versions of original videos. Thus safeguarding copyrights of digital media has become matter of concern. In this paper we propose a video copy detection system which ...

Fast and robust images matching are of vital importance in low-altitude photogrammetric process. Among the most popular features of images matching are currently SIFT and Harris etc. For time-critical applications such as disaster monitoring, the SIFT features extraction are too slow, and the location accuracy of SIFT and Harris is insufficient in photogrammetric process. In this paper, we pres...

This paper introduces D-SIFT, a Web-based browser application that provides untrained users in Formal Concept Analysis with practical and intuitive access to core analysis functionality in Formal Concept Analysis. D-SIFT is an information systems architecture that supports natural search processes over a predefined database schema and its attribute values. This enables the user to build concept...

Image matching using feature extraction is an important issue in computer vision tasks. The main drawback of matching process is the bottleneck problem that rapidly appeared when the number of features increased. This paper produced an adaptive approach to improve Scale Invariant Feature Transform (SIFT) matching. The main idea is to increase the number of SIFT points by using Adaptive PCA in w...