100,466 research outputs found
GeoSay: A Geometric Saliency for Extracting Buildings in Remote Sensing Images
Automatic extraction of buildings in remote sensing images is an important
but challenging task and finds many applications in different fields such as
urban planning, navigation and so on. This paper addresses the problem of
buildings extraction in very high-spatial-resolution (VHSR) remote sensing (RS)
images, whose spatial resolution is often up to half meters and provides rich
information about buildings. Based on the observation that buildings in VHSR-RS
images are always more distinguishable in geometry than in texture or spectral
domain, this paper proposes a geometric building index (GBI) for accurate
building extraction, by computing the geometric saliency from VHSR-RS images.
More precisely, given an image, the geometric saliency is derived from a
mid-level geometric representations based on meaningful junctions that can
locally describe geometrical structures of images. The resulting GBI is finally
measured by integrating the derived geometric saliency of buildings.
Experiments on three public and commonly used datasets demonstrate that the
proposed GBI achieves the state-of-the-art performance and shows impressive
generalization capability. Additionally, GBI preserves both the exact position
and accurate shape of single buildings compared to existing methods
Multi-dimensional modelling for the national mapping agency: a discussion of initial ideas, considerations, and challenges
The Ordnance Survey, the National Mapping Agency (NMA) for Great Britain, has recently
begun to research the possible extension of its 2-dimensional geographic information into a
multi-dimensional environment. Such a move creates a number of data creation and storage
issues which the NMA must consider. Many of these issues are highly relevant to all NMA’s
and their customers alike, and are presented and explored here.
This paper offers a discussion of initial considerations which NMA’s face in the creation of
multi-dimensional datasets. Such issues include assessing which objects should be mapped in
3 dimensions by a National Mapping Agency, what should be sensibly represented
dynamically, and whether resolution of multi-dimensional models should change over space.
This paper also offers some preliminary suggestions for the optimal creation method for any
future enhanced national height model for the Ordnance Survey. This discussion includes
examples of problem areas and issues in both the extraction of 3-D data and in the
topological reconstruction of such. 3-D feature extraction is not a new problem. However, the
degree of automation which may be achieved and the suitability of current techniques for
NMA’s remains a largely unchartered research area, which this research aims to tackle.
The issues presented in this paper require immediate research, and if solved adequately
would mark a cartographic paradigm shift in the communication of geographic information –
and could signify the beginning of the way in which NMA’s both present and interact with
their customers in the future
Building recognition on subregion’s multi-scale gist feature extraction and corresponding columns information based dimensionality reduction
Peer reviewedPublisher PD
Local Defects in colloidal quantum dot thin films measured via spatially resolved multi-modal optoelectronic spectroscopy.
The morphology, chemical composition, and electronic uniformity of thin-film solution-processed optoelectronics are believed to greatly affect device performance. Although scanning probe microscopies can address variations on the micrometer scale, the field of view is still limited to well under the typical device area, as well as the size of extrinsic defects introduced during fabrication. Herein, a micrometer-resolution 2D characterization method with millimeter-scale field of view is demonstrated, which simultaneously collects photoluminescence spectra, photocurrent transients, and photovoltage transients. This high-resolution morphology mapping is used to quantify the distribution and strength of the local optoelectronic property variations in colloidal quantum dot solar cells due to film defects, physical damage, and contaminants across nearly the entire test device area, and the extent to which these variations account for overall performance losses. It is found that macroscopic defects have effects that are confined to their localized areas, rarely prove fatal for device performance, and are largely not responsible for device shunting. Moreover, quantitative analysis based on statistical partitioning methods of such data is used to show how defect identification can be automated while identifying variations in underlying properties such as mobilities and recombination strengths and the mechanisms by which they govern device behavior.DMR-1807342 - National Science Foundation; Hopkins Extreme Materials InstituteAccepted manuscrip
DC-image for real time compressed video matching
This chapter presents a suggested framework for video matching based on local features extracted from the DC-image of MPEG compressed videos, without full decompression. In addition, the relevant arguments and supporting evidences are discussed. Several local feature detectors will be examined to select the best for matching using the DC-image. Two experiments are carried to support the above. The first is comparing between the DC-image and I-frame, in terms of matching performance and computation complexity. The second experiment compares between using local features and global features regarding compressed video matching with respect to the DC-image. The results confirmed that the use of DC-image, despite its highly reduced size, it is promising as it produces higher matching precision, compared to the full I-frame. Also, SIFT, as a local feature, outperforms most of the standard global features. On the other hand, its computation complexity is relatively higher, but it is still within the real-time margin which leaves a space for further optimizations that can be done to improve this computation complexity
Video matching using DC-image and local features
This paper presents a suggested framework for video matching based on local features extracted from the DCimage of MPEG compressed videos, without decompression. The relevant arguments and supporting evidences are discussed for developing video similarity techniques that works directly on compressed videos, without decompression, and especially utilising small size images. Two experiments are carried to support the above. The first is comparing between the DC-image and I-frame, in terms of matching performance and the corresponding computation complexity. The second experiment compares between using local features and global features in video matching, especially in the compressed domain and with the small size images. The results confirmed that the use of DC-image, despite its highly reduced size, is promising as it produces at least similar (if not better) matching precision, compared to the full I-frame. Also, using SIFT, as a local feature, outperforms precision of most of the standard global features. On the other hand, its computation complexity is relatively higher, but it is still within the realtime margin. There are also various optimisations that can be done to improve this computation complexity
Digital Image Access & Retrieval
The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio
Accurate and reliable segmentation of the optic disc in digital fundus images
We describe a complete pipeline for the detection and accurate automatic segmentation of the optic disc in digital fundus images. This procedure provides separation of vascular information and accurate inpainting of vessel-removed images, symmetry-based optic disc localization, and fitting of incrementally complex contour models at increasing resolutions using information related to inpainted images and vessel masks. Validation experiments, performed on a large dataset of images of healthy and pathological eyes, annotated by experts and partially graded with a quality label, demonstrate the good performances of the proposed approach. The method is able to detect the optic disc and trace its contours better than the other systems presented in the literature and tested on the same data. The average error in the obtained contour masks is reasonably close to the interoperator errors and suitable for practical applications. The optic disc segmentation pipeline is currently integrated in a complete software suite for the semiautomatic quantification of retinal vessel properties from fundus camera images (VAMPIRE)
- …