scholarly journals A multi-resolution data structure for two-dimensional Morse-Smale functions

2004 ◽  
Author(s):  
P.-T. Bremer ◽  
H. Edelsbrunner ◽  
B. Hamann ◽  
V. Pascucci
Keyword(s):  
Data Structure ◽  
Two Dimensional ◽  
Resolution Data

An efficient disk based data structure for rapid searching of quantitative two-dimensional gel databases

1993 ◽  
Vol 14 (1) ◽  
pp. 1341-1350 ◽  
Author(s):  
Peter F. Lemkin ◽  
Yecheng Wu ◽  
Kyle Upton
Keyword(s):  
Data Structure ◽  
Two Dimensional

scholarly journals The GeoHashTree: a multi-resolution data structure for the management of point clouds

2014 ◽  
Author(s):  
N Sabo ◽  
A Beaulieu ◽  
D Bélanger ◽  
Y Belzile ◽  
B Piché
Keyword(s):  
Data Structure ◽  
Point Clouds ◽  
Resolution Data

Data-base techniques for multiple two-dimensional polyacrylamide gel electrophoresis analyses.

1980 ◽  
Vol 26 (10) ◽  
pp. 1403-1412 ◽  
Author(s):  
L E Lipkin ◽  
P F Lemkin
Keyword(s):  
Data Structure ◽  
Data Base ◽  
Polyacrylamide Gel Electrophoresis ◽  
Local Alignment ◽  
National Bureau ◽  
Two Dimensional ◽  
Display System ◽  
Interactive Display ◽  
Management Procedures ◽  
Computer Controlled

Abstract Two-dimensional protein electrophoresis can benefit from a powerful set of computer-supported image processing and data structure/management procedures. Detection of quantitative differences is complicated by local inhomogeneities in the polyacrylamide base; biochemical changes and variations in temperature and preparative technique also make the between-gel density and x-y coordinate correspondences quite imprecise. The program presented here provides local alignment and computer-controlled variable “flicker” rates for multiple gels, with use of an interactive display system. Manual spot densitometry, referred to a National Bureau of Standards density wedge, can be complemented by a set of automatic densitometry routines for previously established lists of spots. The ability to establish a set of local landmarks, either by included standards or user identification, provides a basis for automatic n-way gel comparison for subsets or for the entire set of spots. Automatic segmentatin algorithms allow isolatin of spots and separation of touching and partially overlapping regions. Various analytical and statistical facilities are part of the user’s access to the interactively developed data base. The data-structure and image-manipulation techniques developed here allow for user-directed and heuristic comparisons with online presentation of intermediate and final results.

A Fast Template Matching Algorithm Based on Wavelet Coefficient Projection Transform

2011 ◽  
Vol 48-49 ◽  
pp. 21-24 ◽  
Author(s):  
Xian Ping Fu ◽  
Sheng Long Liao
Keyword(s):  
Computer Vision ◽  
Data Structure ◽  
Template Matching ◽  
Performance Enhancement ◽  
Wavelet Coefficient ◽  
Target Position ◽  
Similarity Matching ◽  
Structure Algorithm ◽  
Searching Ability ◽  
Resolution Data

As the electronic industry advances rapidly toward automatic manufacturing smaller, faster, and cheaper products, computer vision play more important role in IC packaging technology than before. One of the important tasks of computer vision is finding target position through similarity matching. Similarity matching requires distance computation of feature vectors for each target image. In this paper we propose a projection transform of wavelet coefficient based multi resolution data-structure algorithm for faster template matching, a position sequence of local sharp variation points in such signals is recorded as features. The proposed approach reduces the number of computation by around 70% over multi resolution data structure algorithm. We use the proposed approach to match similarity between wavelet parameters histograms for image matching. It is noticeable that the proposed fast algorithm provides not only the same retrieval results as the exhaustive search, but also a faster searching ability than existing fast algorithms. The proposed approach can be easily combined with existing algorithms for further performance enhancement.

THE QUALITATIVE TREATMENT OF SPATIAL DATA

2007 ◽  
Vol 16 (04) ◽  
pp. 661-682 ◽  
Author(s):  
KAZUKO TAKAHASHI ◽  
TAKAO SUMITOMO
Keyword(s):  
Data Structure ◽  
Spatial Data ◽  
Spatial Reasoning ◽  
Symbolic Representation ◽  
Two Dimensional ◽  
Efficient Treatment ◽  
Dimensional Plane ◽  
Topological Reasoning ◽  
Qualitative Representation ◽  
New Framework

This paper aims at an efficient treatment of spatial data using qualitative representation. We propose a new framework called PLCA, which provides a symbolic representation for the figure in a two-dimensional plane, focusing on the connections between regions. It is based on four simple objects: points(P), lines(L), circuits(C) and areas(A). The entire figure is represented as a combination of these objects. Pairs of areas, circuits or lines never cross. The simple, clear data structure based on objects makes the system feasible and easy to implement. A PLCA expression can be subject to topological reasoning such as judging the connection patterns of areas. We define the operations of area integration and area division on a PLCA expression. These operations preserve the consistency of the expression, and correspond to real actions on the figures. We can add attributes to each object, such as the properties that hold on an area or that an object represents, and make an attributed PLCA. The operations of area integration/division on an attributed PLCA correspond to the alteration of the classification level of objects, and semantic spatial reasoning can be performed on an attributed PLCA.

scholarly journals An efficient data structure for dynamic two-dimensional reconfiguration

2017 ◽  
Vol 75 ◽  
pp. 15-25 ◽  
Author(s):  
Sándor P. Fekete ◽  
Jan-Marc Reinhardt ◽  
Christian Scheffer
Keyword(s):  
Data Structure ◽  
Two Dimensional ◽  
Efficient Data

A LINEAR SPACE DATA STRUCTURE FOR ORTHOGONAL RANGE REPORTING AND EMPTINESS QUERIES

2009 ◽  
Vol 19 (01) ◽  
pp. 1-15 ◽  
Author(s):  
YAKOV NEKRICH
Keyword(s):  
Data Structure ◽  
Linear Space ◽  
Unit Cost ◽  
Two Dimensional ◽  
Dynamic Data ◽  
Model Of Computation ◽  
Space Data ◽  
Dynamic Data Structure

In this paper we present a linear space dynamic data structure for two-dimensional orthogonal range reporting and emptiness queries. This data structure answers range reporting queries in time [Formula: see text] for any ε > 0 and k the size of the answer. Our data structure also supports emptiness and one-reporting queries in time O( log n log log n). The model of computation used in this paper is a unit-cost RAM model.

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