scholarly journals A Privacy-Protected Image Retrieval Scheme for Fast and Secure Image Search

Symmetry ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 282 ◽  
Author(s):  
Anyu Du ◽  
Liejun Wang ◽  
Shuli Cheng ◽  
Naixiang Ao
Keyword(s):  
Image Retrieval ◽  
Multimedia Technology ◽  
Hyperchaotic System ◽  
Algorithm Performance ◽  
Secure Access ◽  
Hash Algorithm ◽  
Control Scheme ◽  
Retrieval Efficiency ◽  
Retrieval Scheme ◽  
Improve Algorithm

With the development of multimedia technology, the secure image retrieval scheme has become a hot research topic. However, how to further improve algorithm performance in the ciphertext needs to be further explored. In this paper, we propose a secure image retrieval scheme based on a deep hash algorithm for index encryption and an improved 4-Dimensional(4-D)hyperchaotic system. The main contributions of this paper are as follows: (1) A novel secure retrieval scheme is proposed to control data transmission. (2) An improved 4-D hyperchaotic system is proposed to preserve privacy. (3) We propose an improved deep pairwise-supervised hashing (DPSH) algorithm and secure kNN to perform index encryption and propose an improved loss function to train the network model. (4) A secure access control scheme is shown, which aims to achieve secure access for users. The experimental results show that the proposed scheme has better retrieval efficiency and better security.

EXPLOITING THE MEMORY HIERARCHY OF MULTICORE SYSTEMS FOR PARALLEL TRIANGULATION REFINEMENT

2012 ◽  
Vol 22 (03) ◽  
pp. 1250007 ◽  
Author(s):  
PEDRO RODRÍGUEZ ◽  
MARÍA CECILIA RIVARA ◽  
ISAAC D. SCHERSON
Keyword(s):  
Parallel Implementation ◽  
Memory Hierarchy ◽  
Random Selection ◽  
Multicore Systems ◽  
Algorithm Performance ◽  
Bisection Algorithm ◽  
Improve Algorithm ◽  
Triangulation Refinement ◽  
Selection Of

A novel parallelization of the Lepp-bisection algorithm for triangulation refinement on multicore systems is presented. Randomization and wise use of the memory hierarchy are shown to highly improve algorithm performance. Given a list of selected triangles to be refined, random selection of candidates together with pre-fetching of Lepp-submeshes lead to a scalable and efficient multi-core parallel implementation. The quality of the refinement is shown to be preserved.

Fuzzy Heuristics for Sequential Linear Programming

1998 ◽  
Vol 120 (1) ◽  
pp. 17-23 ◽  
Author(s):  
E. L. Mulkay ◽  
S. S. Rao
Keyword(s):  
Fuzzy Logic ◽  
Linear Programming ◽  
Path Following ◽  
Human Observer ◽  
Sequential Linear Programming ◽  
Algorithm Performance ◽  
Primal Dual ◽  
Improve Algorithm ◽  
Range Of Values ◽  
Better Than

Numerical implementations of optimization algorithms often use parameters whose values are not strictly determined by the derivation of the algorithm, but must fall in some appropriate range of values. This work describes how fuzzy logic can be used to “control” such parameters to improve algorithm performance. This concept is shown with the use of sequential linear programming (SLP) due to its simplicity in implementation. The algorithm presented in this paper implements heuristics to improve the behavior of SLP based on current iterate values of design constraints and changes in search direction. Fuzzy logic is used to implement the heuristics in a form similar to what a human observer would do. An efficient algorithm, known as the infeasible primal-dual path-following interior-point method, is used for solving the sequence of LP problems. Four numerical examples are presented to show that the proposed SLP algorithm consistently performs better than the standard SLP algorithm.

scholarly journals Environmental Analysis of GOES-R Proving Ground Convection-Initiation Forecasting Algorithms

2015 ◽  
Vol 54 (7) ◽  
pp. 1637-1662 ◽  
Author(s):  
Jason M. Apke ◽  
Daniel Nietfeld ◽  
Mark R. Anderson
Keyword(s):  
Environmental Variables ◽  
Environmental Influences ◽  
Principal Component ◽  
University Of Alabama ◽  
Algorithm Performance ◽  
University Of Wisconsin ◽  
Improve Algorithm ◽  
Convection Initiation ◽  
The University

AbstractEnhanced temporal and spatial resolution of the Geostationary Operational Environmental Satellite–R Series (GOES-R) will allow for the use of cloud-top-cooling-based convection-initiation (CI) forecasting algorithms. Two such algorithms have been created on the current generation of GOES: the University of Wisconsin cloud-top-cooling algorithm (UWCTC) and the University of Alabama in Huntsville’s satellite convection analysis and tracking algorithm (SATCAST). Preliminary analyses of algorithm products have led to speculation over preconvective environmental influences on algorithm performance. An objective validation approach is developed to separate algorithm products into positive and false indications. Seventeen preconvective environmental variables are examined for the positive and false indications to improve algorithm output. The total dataset consists of two time periods in the late convective season of 2012 and the early convective season of 2013. Data are examined for environmental relationships using principal component analysis (PCA) and quadratic discriminant analysis (QDA). Data fusion by QDA is tested for SATCAST and UWCTC on five separate case-study days to determine whether application of environmental variables improves satellite-based CI forecasting. PCA and significance testing revealed that positive indications favored environments with greater vertically integrated instability (CAPE), less stability (CIN), and more low-level convergence. QDA improved both algorithms on all five case studies using significantly different variables. This study provides an examination of environmental influences on the performance of GOES-R Proving Ground CI forecasting algorithms and shows that integration of QDA in the cloud-top-cooling-based algorithms using environmental variables will ultimately generate a more skillful product.

A FAST TWO-STAGE CONTENT-BASED IMAGE RETRIEVAL APPROACH IN THE DCT DOMAIN

2008 ◽  
Vol 22 (04) ◽  
pp. 765-781 ◽  
Author(s):  
TIENWEI TSAI ◽  
YO-PING HUANG ◽  
TE-WEI CHIANG
Keyword(s):  
Image Retrieval ◽  
High Efficiency ◽  
Feature Space ◽  
Content Based Image Retrieval ◽  
Two Stage ◽  
Feature Extraction Method ◽  
Domain Specific ◽  
Retrieval Scheme ◽  
Domain Specific Knowledge ◽  
Distinct Features

In this paper, a two-stage content-based image retrieval (CBIR) approach is proposed to improve the retrieval performance. To develop a general retrieval scheme which is less dependent on domain-specific knowledge, the discrete cosine transform (DCT) is employed as a feature extraction method. In establishing the database, the DC coefficients of Y, U and V components are quantized such that the feature space is partitioned into a finite number of grids, each of which is mapped to a grid code (GC). When querying an image, at coarse classification stage, the grid-based classification (GBC) and the distance threshold pruning (DTP) serve as a filter to remove those candidates with widely distinct features. At the fine classification stage, only the remaining candidates need to be computed for the detailed similarity comparison. The experimental results show that both high efficacy and high efficiency can be achieved simultaneously using the proposed two-stage approach.

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