Monitoring and remote sensing of the street lighting system using computer vision and image processing techniques for the purpose of mechanized blackouts (development phase)

2013 ◽  
Author(s):  
P.N. Zanjani ◽  
M. Bahadori ◽  
M. Hashemi
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Computer Vision ◽  
Development Phase ◽  
Lighting System ◽  
Street Lighting ◽  
Image Processing Techniques ◽  
Processing Techniques

scholarly journals Clay-Based Brick Porosity Estimation Using Image Processing Techniques

2019 ◽  
Vol 29 (1) ◽  
pp. 1226-1234
Author(s):  
Safa Jida ◽  
Hassan Ouallal ◽  
Brahim Aksasse ◽  
Mohammed Ouanan ◽  
Mohamed El Amraoui ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
Image Processing ◽  
Scanning Electron Microscopy ◽  
Computer Vision ◽  
Image Processing Techniques ◽  
Processing Techniques ◽  
Porosity Estimation ◽  
Microscopy Images ◽  
Scanning Electron

Abstract This work intends to apprehend and emphasize the contribution of image-processing techniques and computer vision in the treatment of clay-based material known in Meknes region. One of the various characteristics used to describe clay in a qualitative manner is porosity, as it is considered one of the properties that with “kill or cure” effectiveness. For this purpose, we use scanning electron microscopy images, as they are considered the most powerful tool for characterising the quality of the microscopic pore structure of porous materials. We present various existing methods of segmentation, as we are interested only in pore regions. The results show good matching between physical estimation and Voronoi diagram-based porosity estimation.

scholarly journals Sistem Computer Vision Pengenalan Pola Angka dan Operator Matematika Pada Permainan Kartu Angka Berbasis Jaringan Syaraf Tiruan Perceptron

2018 ◽  
Vol 9 (1) ◽  
Author(s):  
Rian Rahmanda Putra ◽  
Fery Antony
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Vision System ◽  
Computer Vision System ◽  
Image Processing Techniques ◽  
Perceptron Algorithm ◽  
Card Number ◽  
Training Stage ◽  
Processing Techniques ◽  
Real Time Application

<p align="center"><strong><em>Abstract <br /></em></strong></p><p><em>Computer vision is an image processing by a computer to obtain information from image captured through the camera generally used in real-time application. This paper reports on the results of research conducted on computer vision system designed to be able to recognize the image number (0-9) and mathematical operators (addition (+) and subtraction (-)) in a card number figures. Computer vision system designed in this study consists of a camera on the android phone that used to captured images on the card number and the computer that has artificial neural network perceptron algorithm in identifiying images. Both components of the computer vision system are connected wirelessly through the TCP/IP Protocol. At the training stage of Perceptron ANN, 10 samples for each number and mathematical operators are used. Computer vision system built in this study also have several image processing techniques such as greyscalling, thresholding, cropping and resizing. This techniques is used to filter the information from the images captured by camera in order to get the adequate and smaller image to be processed by ANN Perceptron. Stages of testing performed three times. First testing is given picture numbers 0-3, second testing is given picture number 4-7 and third testing is given number 8-9, addition symbol and subtraction symbol. Based on testing result, system built are able to recognize 10 from 12 image rendered with a success rate of 83.33%.</em></p><p><strong><em>Keywords</em></strong><em> : Computer vision, perceptron, card number</em></p><p><em> </em></p><p align="center"><strong><em>Abstrak <br /></em></strong></p><p><em>Computer vision merupakan proses pengolahan citra oleh computer untuk mendapatkan informasi dari citra yang ditangkap melalui kamera yang umumnya digunakan pada aplikasi waktu nyata. Tulisan ini melaporkan tentang hasil penelitian yang dilakukan tentang sistem computer vision yang dirancang untuk dapat mengenali gambar angka (0-9) dan operator matematika(penjumlahan (+) dan pengurangan (-)) pada permainan kartu angka. Sistem computer vision yang dirancang pada penelitian ini terdiri dari kamera pada ponsel android yang digunakan untuk menangkap gambar pada kartu angka dan komputer yang memiliki algoritama Jaringan Syaraf Tiruan Perceptron dalam melakukan identifikasi gambar. Kedua komponen sistem computer vision tersebut dihubungkan memlaui jaringan wireless melalui protocol TCP/IP. Pada tahapan pelatihan JST perceptron, digunakan 10 sample citra untuk masing – masing angka dan operator matematika yang akan dikenali oleh sistem. Pada penelitian ini juga dilakukan tahapan pemrosesan citra sebelum diolah oleh JST Perceptron baik dalam tahapan pelatihan maupun pada saat sistem dijalankan. Tahapan pengolahan citra yang digunakan pada penelitian ini adalah greyscalling, thresholding, cropping dan resizing. Hal ini dilakukan untuk menyaring informasi pada citra yang ditangkap oleh kamera agar didapatkan citra yang berukuran kecil dengan  informasi yang lengkap untuk diproses oleh JST Perceptron. Pada saat sistem diuji coba, diberikan 4 deret kartu angka di depan kamera. Pada pengujian pertama diberikan gambar angka 0-3, pengujian kedua diberikan gambar angka 4-7 dan pada pengujian ketiga diberikan angka 8-9 serta gambar operator penjumlahan dan pengurangan. Berdasarkan pengujian yang dilakukan, sistem computer vision yang dirancang mampu mengenali 10dari 12 gambar yang diberikan dengan tingkat keberhasilan sebesar 83.33%.</em></p><p><strong><em>Kata Kunci </em></strong><em>: computer vision, perceptron, kartu angka</em></p>

A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters

2009 ◽  
Vol 33 (2) ◽  
pp. 183-207 ◽  
Author(s):  
Karen E. Joyce ◽  
Stella E. Belliss ◽  
Sergey V. Samsonov ◽  
Stephen J. McNeill ◽  
Phil J. Glassey
Keyword(s):  
Remote Sensing ◽  
Image Processing ◽  
Emergency Services ◽  
Spatial Information ◽  
Current Status ◽  
Data Types ◽  
Image Processing Techniques ◽  
Rapid Acquisition ◽  
The Status ◽  
Processing Techniques

In the event of a natural disaster, remote sensing is a valuable source of spatial information and its utility has been proven on many occasions around the world. However, there are many different types of hazards experienced worldwide on an annual basis and their remote sensing solutions are equally varied. This paper addresses a number of data types and image processing techniques used to map and monitor earthquakes, faulting, volcanic activity, landslides, flooding, and wildfire, and the damages associated with each. Remote sensing is currently used operationally for some monitoring programs, though there are also difficulties associated with the rapid acquisition of data and provision of a robust product to emergency services as an end-user. The current status of remote sensing as a rapid-response data source is discussed, and some perspectives given on emerging airborne and satellite technologies.

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