scholarly journals An Implementation of Selected Image Processing for Single and Multiple Processors

2019 ◽  
Vol 8 (06) ◽  
pp. 24697-24768
Author(s):  
Wafaa Ahmad Bazzi
Keyword(s):  
Image Processing ◽  
Parallel Computing ◽  
Image Manipulation ◽  
Important Data ◽  
Multiple Processors ◽  
The Given

Image processing contributes on many of the technological advancements today. It is widely used by the developing institutes as well as a source of important data. One of the main things that are considered through this process would be the length of time on dealing with the application of different routines, on these images. Thus, time, being a valuable criterion for the efficiency of the systems, demands a better way for how these images will be managed. With the given situation, the idea of integrating a number of computers to perform image manipulation is considered. This uses the idea of parallel computing.

Matlab and Parallel Computing

2012 ◽  
Vol 17 (4) ◽  
pp. 207-216 ◽  
Author(s):  
Magdalena Szymczyk ◽  
Piotr Szymczyk
Keyword(s):  
Image Processing ◽  
Signal Processing ◽  
Parallel Computing ◽  
Distributed Computing ◽  
Control Systems ◽  
High Performance ◽  
Parallel Applications ◽  
Process Simulations ◽  
Key Features ◽  
Financial Process

Abstract The MATLAB is a technical computing language used in a variety of fields, such as control systems, image and signal processing, visualization, financial process simulations in an easy-to-use environment. MATLAB offers "toolboxes" which are specialized libraries for variety scientific domains, and a simplified interface to high-performance libraries (LAPACK, BLAS, FFTW too). Now MATLAB is enriched by the possibility of parallel computing with the Parallel Computing ToolboxTM and MATLAB Distributed Computing ServerTM. In this article we present some of the key features of MATLAB parallel applications focused on using GPU processors for image processing.

Simulation-Based Scheduling of Waterway Projects Using a Parallel Genetic Algorithm

2015 ◽  
pp. 334-347 ◽  
Author(s):  
Ning Yang ◽  
Shiaaulir Wang ◽  
Paul Schonfeld
Keyword(s):  
Genetic Algorithm ◽  
Parallel Computing ◽  
Message Passing ◽  
Message Passing Interface ◽  
Computation Time ◽  
Parallel Genetic Algorithm ◽  
Simulation Based ◽  
Multiple Processors ◽  
Simulation Based Optimization ◽  
Speed Up

A Parallel Genetic Algorithm (PGA) is used for a simulation-based optimization of waterway project schedules. This PGA is designed to distribute a Genetic Algorithm application over multiple processors in order to speed up the solution search procedure for a very large combinational problem. The proposed PGA is based on a global parallel model, which is also called a master-slave model. A Message-Passing Interface (MPI) is used in developing the parallel computing program. A case study is presented, whose results show how the adaption of a simulation-based optimization algorithm to parallel computing can greatly reduce computation time. Additional techniques which are found to further improve the PGA performance include: (1) choosing an appropriate task distribution method, (2) distributing simulation replications instead of different solutions, (3) avoiding the simulation of duplicate solutions, (4) avoiding running multiple simulations simultaneously in shared-memory processors, and (5) avoiding using multiple processors which belong to different clusters (physical sub-networks).

Research and Performance Analysis on Parallel Computing of Remote Sensing Image Based on MPICH

2013 ◽  
Vol 680 ◽  
pp. 540-545
Author(s):  
Jun Li ◽  
Wei Feng Ma
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Parallel Computing ◽  
Cluster Computing ◽  
Single Mode ◽  
Remote Sensing Image ◽  
Distributed Parallel Computing ◽  
And Performance ◽  
Occurrence Matrix ◽  
Remote Sensing Image Processing

The traditional centralized single mode becomes a “bottleneck” of remote sensing image processing which cannot meet the needs of future remote sensing image processing development. Fortunately, the distributed parallel computing has provided a turning point to the quick calculation of remote sensing image. This paper presents the cluster computing environment based on the MPI, and advances a project of a parallelized design to the gray level co-occurrence matrix algorithm. Moreover, the experimental data, which is due to the parallelized algorithm running in the cluster, is recorded and analyzed in several respects such as different nodes, time, speedup, efficiency and so on. The analyzed result shows that parallel computing cluster based on MPICH can efficiently improve the speed of remote sensing image processing in the case of more complex algorithms. However, when the number of node increases, the consuming time decreases, and the efficiency will decrease at the same time. So, it is rather important to keep the balance between performance and efficiency. The nodes can not be continuously added into computing, when the consuming time can be accepted.

scholarly journals Texture Enhancement Based on the Savitzky-Golay Fractional Differential Operator

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Hamid A. Jalab ◽  
Rabha W. Ibrahim
Keyword(s):  
Image Processing ◽  
Differential Operator ◽  
Fractional Order ◽  
Fractional Operators ◽  
Enhancement Technique ◽  
Fractional Differential Operator ◽  
Weight Window ◽  
Fractional Differential ◽  
Fractional Filter ◽  
The Given

Texture enhancement for digital images is the most important technique in image processing. The purpose of this paper is to design a texture enhancement technique using fractional order Savitzky-Golay differentiator, which leads to generalizing the Savitzky-Golay filter in the sense of the Srivastava-Owa fractional operators. By employing this generalized fractional filter, texture enhancement is introduced. Consequently, it calculates the generalized fractional order derivative of the given image using the sliding weight window over the image. Experimental results show that the operator can extract more subtle information and make the edges more prominent. In general, the capability of the generalized fractional differential will be high because it is sensitive to the subtle fluctuations of values of pixels.

Interactive Image Processing and Manipulation

2007 ◽  
Author(s):  
Stephen S. Nestinger ◽  
Harry H. Cheng
Keyword(s):  
Image Processing ◽  
Rapid Prototyping ◽  
Rapid Development ◽  
Imaging Informatics ◽  
Image Manipulation ◽  
Web Based ◽  
Diverse Range ◽  
Electronic Imaging ◽  
Dynamic Manipulation

Electronic imaging informatics spans a diverse range of applications. These applications would benefit from an interpretive imaging platform, which allows dynamic manipulation and processing of electronic images. Ch is an embeddable C/C++ interpreter that provides an interpretive platform for C/C++ based scripts and programs. Combining Ch with ImageMagick provides the functionality for rapid development of user defined image manipulation and processing applications and scripts. The presented Ch ImageMagick package provides users with the ability to interpretively execute C code based on the ImageMagick C library. This article describes the integration of ImageMagick and Ch. The use of ImageMagick utilities in Ch scripts for rapid prototyping is illustrated. A Web-based example demonstrates the use of Ch and ImageMagick in C based CGI scripting to facilitate the development of Web-based applications involving image manipulation and processing.

Design of Assistance System Based on OpenCV for Color-Blindness

2013 ◽  
Vol 321-324 ◽  
pp. 1098-1101
Author(s):  
Zhan Rong Feng ◽  
Li Xia Wang ◽  
Gang Yao Zhao
Keyword(s):  
Image Processing ◽  
Continuous Improvement ◽  
Color Space ◽  
Color Discrimination ◽  
Color Blindness ◽  
Assistance System ◽  
Rotation Transformation ◽  
Discrimination Capacity ◽  
The Given

With the wide application of image processing as well as continuous improvement of processing means, carrying out rotation transformation of H component of the color space with OpenCV can improve the resolution for color and make up for the color discrimination capacity of the achromat effectively. Experiments have shown that when the type of color-blindness is given and the colors of the image are confusing for the given achromat, rotate the H component by 105~130°, the achromat can identify the colors well.

scholarly journals An Image Processing Based Fungus Detection System for Mangoes

2019 ◽  
Vol 9 (1) ◽  
pp. 3493-3497
Keyword(s):  
Image Processing ◽  
Detection System ◽  
Health Problems ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
High Yield ◽  
Data Set ◽  
Different Color ◽  
The Given

Fruits which grow with high yield in many states of India are rich in proteins. But due to addition of excess pesticides and chemicals intake of these fruits lead to serious health problems. It is necessary to identify the presence of chemical in the fruits before consuming it. In this project we have planned to develop an image processing technique to analyze whether the fruit is free from chemicals and fungus. In our paper, we have implemented MATLAB used as well as fungus present in the fruit. We capture the images of the fruit or we use datasets and train the database with different color-based changes that happen after adding chemicals to the fruit. The enhancement process is carried out in the captured image. Then image is segmented to hit the regions with affected spots in the fruit. K-means method is used to carry out the segmentation process. The input image is compared with the given data set for training to identify the images. In this way unhealthy fruits can be identified and the affected spots in the fruit can be detected.

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