6,021 research outputs found
A programme to determine the exact interior of any connected digital picture
Region filling is one of the most important and fundamental operations in
computer graphics and image processing. Many filling algorithms and their
implementations are based on the Euclidean geometry, which are then translated
into computational models moving carelessly from the continuous to the finite
discrete space of the computer. The consequences of this approach is that most
implementations fail when tested for challenging degenerate and nearly
degenerate regions. We present a correct integer-only procedure that works for
all connected digital pictures. It finds all possible interior points, which
are then displayed and stored in a locating matrix. Namely, we present a
filling and locating procedure that can be used in computer graphics and image
processing applications
Raster graphics extensions to the core system
A conceptual model of raster graphics systems was developed. The model integrates core-like graphics package concepts with contemporary raster display architectures. The conceptual model of raster graphics introduces multiple pixel matrices with associated index tables
Synthetic 3D Pap smear nucleus generation
GĂłmez Aguilar, S. (2010). Synthetic 3D Pap smear nucleus generation. http://hdl.handle.net/10251/10215.Archivo delegad
Development of computer software to analyze entire LANDSAT scenes and to summarize classification results of variable-size polygons
The Forest Pest Management Division (FPMD) of the Pennsylvania Bureau of Forestry has the responsibility for conducting annual surveys of the State's forest lands to accurately detect, map, and appraise forest insect infestations. A standardized, timely, and cost-effective method of accurately surveying forests and their condition should enhance the probability of suppressing infestations. The repetitive and synoptic coverage provided by LANDSAT (formerly ERTS) makes such satellite-derived data potentially attractive as a survey medium for monitoring forest insect damage over large areas. Forest Pest Management Division personnel have expressed keen interest in LANDSAT data and have informally cooperated with NASA/Goddard Space Flight Center (GSFC) since 1976 in the development of techniques to facilitate their use. The results of this work indicate that it may be feasible to use LANDSAT digital data to conduct annual surveys of insect defoliation of hardwood forests
Efficient Irregular Wavefront Propagation Algorithms on Hybrid CPU-GPU Machines
In this paper, we address the problem of efficient execution of a computation
pattern, referred to here as the irregular wavefront propagation pattern
(IWPP), on hybrid systems with multiple CPUs and GPUs. The IWPP is common in
several image processing operations. In the IWPP, data elements in the
wavefront propagate waves to their neighboring elements on a grid if a
propagation condition is satisfied. Elements receiving the propagated waves
become part of the wavefront. This pattern results in irregular data accesses
and computations. We develop and evaluate strategies for efficient computation
and propagation of wavefronts using a multi-level queue structure. This queue
structure improves the utilization of fast memories in a GPU and reduces
synchronization overheads. We also develop a tile-based parallelization
strategy to support execution on multiple CPUs and GPUs. We evaluate our
approaches on a state-of-the-art GPU accelerated machine (equipped with 3 GPUs
and 2 multicore CPUs) using the IWPP implementations of two widely used image
processing operations: morphological reconstruction and euclidean distance
transform. Our results show significant performance improvements on GPUs. The
use of multiple CPUs and GPUs cooperatively attains speedups of 50x and 85x
with respect to single core CPU executions for morphological reconstruction and
euclidean distance transform, respectively.Comment: 37 pages, 16 figure
Geocoded data structures and their applications to Earth science investigations
A geocoded data structure is a means for digitally representing a geographically referenced map or image. The characteristics of representative cellular, linked, and hybrid geocoded data structures are reviewed. The data processing requirements of Earth science projects at the Goddard Space Flight Center and the basic tools of geographic data processing are described. Specific ways that new geocoded data structures can be used to adapt these tools to scientists' needs are presented. These include: expanding analysis and modeling capabilities; simplifying the merging of data sets from diverse sources; and saving computer storage space
Faster Calculation of Superquadric Shapes
Nonparametric methods of calculating points on the curve produce the recently introduced superquadric objects at great savings in time
Incremental Distance Transforms (IDT)
A new generic scheme for incremental implementations of distance transforms (DT) is presented: Incremental Distance Transforms (IDT). This scheme is applied on the cityblock, Chamfer, and three recent exact Euclidean DT (E2DT). A benchmark shows that for all five DT, the incremental implementation results in a significant speedup: 3.4Ăâ10Ă. However, significant differences (i.e., up to 12.5Ă) among the DT remain present. The FEED transform, one of the recent E2DT, even showed to be faster than both city-block and Chamfer DT. So, through a very efficient incremental processing scheme for DT, a relief is found for E2DTâs computational burden
Scalable Estimation of Precision Maps in a MapReduce Framework
This paper presents a large-scale strip adjustment method for LiDAR mobile
mapping data, yielding highly precise maps. It uses several concepts to achieve
scalability. First, an efficient graph-based pre-segmentation is used, which
directly operates on LiDAR scan strip data, rather than on point clouds.
Second, observation equations are obtained from a dense matching, which is
formulated in terms of an estimation of a latent map. As a result of this
formulation, the number of observation equations is not quadratic, but rather
linear in the number of scan strips. Third, the dynamic Bayes network, which
results from all observation and condition equations, is partitioned into two
sub-networks. Consequently, the estimation matrices for all position and
orientation corrections are linear instead of quadratic in the number of
unknowns and can be solved very efficiently using an alternating least squares
approach. It is shown how this approach can be mapped to a standard key/value
MapReduce implementation, where each of the processing nodes operates
independently on small chunks of data, leading to essentially linear
scalability. Results are demonstrated for a dataset of one billion measured
LiDAR points and 278,000 unknowns, leading to maps with a precision of a few
millimeters.Comment: ACM SIGSPATIAL'16, October 31-November 03, 2016, Burlingame, CA, US
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