scholarly journals IoT Based Image Processing Filters

2021 ◽  
Vol 1 (4) ◽  
pp. 1-13
Author(s):  
Noor Abbas ◽  
Mohamed Ibrahim Shujaa ◽  
Entithaar Mhwes Zghair
Keyword(s):  
Image Processing ◽  
Internet Of Things ◽  
Color Image ◽  
Processing System ◽  
System Generator ◽  
Black And White ◽  
The Common ◽  
Image Processing Algorithms ◽  
Practical Life ◽  
Main Component

Internet of things (IoT) becomes the backbone of the advanced countries and it has a real contribute to exchange the traditional style or way of practical life, even personal life into smart style, with (IoT) technology the life become more and more easy and professional. internet of things achieves various applications coordinate with sensors and standard protocols to apply what is called machine -to- machine connection (M2M), in this paper we will talk more about the concept of (M2M), the main component of internet of things and finally the common protocols that is used in network, in addition to that this work present an IOT operation with processing system using camera for capturing image and Xilinx system generator(XSG)models for designing  image processing algorithms and the result of  the processing is an image with black and white for edge detection and Thresholding models  and gray color image for gray enhancement model.

scholarly journals IoT Based Image Processing Filters

2021 ◽  
Vol 2 (4) ◽  
pp. 1-13
Author(s):  
Noor Abbas ◽  
Mohamed Ibrahim Shujaa ◽  
Entithaar Mhwes Zghair
Keyword(s):  
Image Processing ◽  
Internet Of Things ◽  
Color Image ◽  
Processing System ◽  
System Generator ◽  
Black And White ◽  
The Common ◽  
Image Processing Algorithms ◽  
Practical Life ◽  
Main Component

Internet of things (IoT) becomes the backbone of the advanced countries and it has a real contribute to exchange the traditional style or way of practical life, even personal life into smart style, with (IoT) technology the life become more and more easy and professional. internet of things achieves various applications coordinate with sensors and standard protocols to apply what is called machine -to- machine connection (M2M), in this paper we will talk more about the concept of (M2M), the main component of internet of things and finally the common protocols that is used in network, in addition to that this work present an IOT operation with processing system using camera for capturing image and Xilinx system generator(XSG)models for designing  image processing algorithms and the result of  the processing is an image with black and white for edge detection and Thresholding models  and gray color image for gray enhancement model.

scholarly journals Convolutional neural network in the images colorization problem

2019 ◽  
pp. 340-353
Author(s):  
M V Bulygin ◽  
M M Gayanova ◽  
A M Vulfin ◽  
A D Kirillova ◽  
R Ch Gayanov
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Image Processing ◽  
Processing System ◽  
Black And White ◽  
Convolutional Networks ◽  
Advantages And Disadvantages ◽  
The Neural Network ◽  
Image Processing Algorithms ◽  
Processing Algorithms

Object of the research are modern structures and architectures of neural networks for image processing. Goal of the work is improving the existing image processing algorithms based on the extraction and compression of features using neural networks using the colorization of black and white images as an example. The subject of the work is the algorithms of neural network image processing using heterogeneous convolutional networks in the colorization problem. The analysis of image processing algorithms with the help of neural networks is carried out, the structure of the neural network processing system for image colorization is developed, colorization algorithms are developed and implemented. To analyze the proposed algorithms, a computational experiment was conducted and conclusions were drawn about the advantages and disadvantages of each of the algorithms.

Image Processing for Electron Microscope Investigations of Materials

1983 ◽  
Vol 31 ◽  
Author(s):  
William Krakow
Keyword(s):  
Image Processing ◽  
Text Processing ◽  
Computer Control ◽  
Full Range ◽  
Computer Software ◽  
Processing System ◽  
Image Motion ◽  
Hard Copy ◽  
Digital Television ◽  
Main Component

ABSTRACTA time shared television digital image processing system has been developed for on-line electron microscopy and uses a large mainframe computer. The main component of the system is a digital television frame store which has many standard features for digital analysis such as: digitization, zoom and pan, arithmetic and Boolean processors, alphanumeric generators and so on. Images can be acquired at atomic resolution from a TEM, analyzed in real time and hard copy slides made under full computer control. A full range of computer software has been developed or modified from existing software and is generally compatible with IBM Fortran compilers. Some of the areas where extensive menu driven software has been developed are: particle size and feature analysis, algebraic and geometric image manipulations, Fourier analysis, digitization and process control, image contrast correction, text processing, etc. A number of applications areas have been explored which include: the structure of Si/SiO2interfaces; nucleation of Au on rocksalt; the formation of hexatic structures from amorphous phases under shear, tension and compression; analysis of atomic surface structure and image motion and the analysis of field ion micrographs of amorphous structures. Several of these areas will be discussed in the context of image processing and materials characterization.

Research on the Multi-Spectrum Imaging System Based on Vision Technology

2012 ◽  
Vol 443-444 ◽  
pp. 488-494
Author(s):  
Xuan Hong Jin ◽  
Zheng Yang Zhou ◽  
Ran Xu
Keyword(s):  
Image Processing ◽  
Virtual Instrument ◽  
Imaging System ◽  
Color Image ◽  
Processing System ◽  
New Type ◽  
Spectrum Imaging ◽  
Processing Software ◽  
Image Processing Software ◽  
Labview Platform

This paper introduces an acquiring and processing system of a new type of optical spectrometer based on vision technology. It mainly introduces the hardware structure to acquire the spectrums dispersed by the spectrometer, and the multi-spectrum image processing software as well. Of the different spectrum wavelengths ranges from 400nm to 740nm, the system can create both the color image and the 68 channels gray scale image. Virtual instruments technology is introduced into this system and it makes programming easier and faster by combining virtual instrument and vision technology. The programming of the image processing software uses LabVIEW platform.

Feature Extraction Algorithms to Color Image

2017 ◽  
pp. 27-50
Author(s):  
QingE Wu ◽  
Weidong Yang
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Color Image ◽  
Probabilistic Algorithm ◽  
Corner Points ◽  
Case Surgery ◽  
Image Processing Algorithms ◽  
Processing Algorithms ◽  
Different Color ◽  
Better Than

The existing image processing algorithms mainly studied on feature extraction of gray image with one-dimensional parameter, such as edges, corners. However, the extraction of some characteristic points to color image with three-dimensional parameters, such as the extraction of color edge, corner points, inflection points, etc., is an image problem to be urgently solved. In order to carry out a fast and accurate feature extraction on color image, this paper proposes two types of extraction algorithms to color edge and corner points of color image, i.e., similar color segment algorithm and pixel probabilistic algorithm, compares with the two algorithms, gives the two algorithms are used to different color distribution situations, as well as shows the extraction effect of color by the combination of the two algorithms, moreover, gives the contrast experiment and effect analysis of the two algorithms. To compare the similar color segment algorithm with the probabilistic algorithm, experimental results show that the similar color segment algorithm is better than the pixel probabilistic algorithm under the more obvious color edge, because it has the better edge detection, stronger anti-noise ability, faster processing speed and other advantages. Under the transition phase of color edge is gentle or color edge is no clear, the image detection effect of the pixel probabilistic algorithm is better than that of the similar color segment algorithm. But the combinative effect of the two algorithms is the best in this case, which is more close to the color effect of original image. Moreover, this paper analyzes the performance of the similar color segment algorithm, and gives the comparison of the proposed two algorithms and existing classical algorithms used usually to feature extraction of color image. The two algorithms proposed and these researches development in this paper have not only enriched the contents of image processing algorithms, but also provide a solution tool for image segmentation, feature extraction to target, precise positioning, etc., such as extraction of complexion, physiological color photographs processing, feature extraction of ionosphere, detection and extraction of biological composition of oceans, to be applied to a lots of departments, such as the police, hospital departments, surgery, polar department, and so on, as well as provide a way of thinking for the rapid, accurate detection of case, surgery, scientific research information search.

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