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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
ISSN : 25024752     EISSN : 25024760     DOI : -
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Articles 67 Documents
Search results for , issue "Vol 19, No 3: September 2020" : 67 Documents clear
Recognition of handwritten Arabic (Indian) numerals using skeleton matching Bassam Alqaralleh; Malek Zakarya Alksasbeh; Tamer Abukhalil; Harbi Almahafzah; Tawfiq Al Rawashdeh
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1461-1468

Abstract

This paper brings into discussion the problem of recognizing Arabic numbers using a monocular camera as the only sensor. When a digital image is presented in this application, optical character recognition (OCR) can be exploited to comprehend numerical data. However, there has been a limited success when applied to the handwritten Arabic (Indian) numbers. This paper aims to overcome this limitation and introduces optical character recognition system based on skeleton matching. The proposed approach is used for handwritten Arabic numbers only. The experimental results indicate the effectiveness of the proposed optical character recognition system even for numbers written in worst case. The right system achieves a recognition rate of 99.3 %.
Improvement of cluster-based WSN protocol using fuzzy logic Jong-Yong Lee; Daesung Lee
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1540-1547

Abstract

A wireless sensor network is a collection of wireless nodes with sensor devices that can collect data from the real world. This is because sensor nodes usually use limited-powered batteries. Therefore, if the battery on the sensor node is exhausted, the node will no longer be available. If the battery on some nodes is discharged, the sensor network will not work properly. To maintain sensor network system, there are many wireless sensor network protocols to increase energy efficiency of nodes. One of the energy-efficient methods is cluster-based protocols. These protocols divide the sensor fields into clusters and send and receive data between nodes. Thus, depending on how the cluster is constructed, the network's lifetime may be reduced or increased. Cluster-based protocols cannot always be optimal cluster configurations. These problems have been improved using fuzzy logic. In general, fuzzy logic is used to elect cluster heads based on node residual energy, node concentration and node centrality. However, it is possible that nodes close to each other at a high density area are elected as cluster heads. In this paper, we propose a method to consider the number of adjacent cluster heads instead of Node Concentration to improve the problem.
Miniaturized ultra-wideband coplanarwaveguide lowpass filter with extended stop band Elmahjouby Sghir; Ahmed Errkik; Jamal Zbitou; Otman Oulhaj; Ahmed Lakhssassi; Mohamed Latrach
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1415-1419

Abstract

In this article, we propose a novel design of large rejected band of miniaturized ultra wide band (UWB) of a planar CPW low pass filter “LPF” based on the use of periodic elements of ‘e’ slots. The goal of this work is to develop a new structure of Low Pass Filter with the following criterion: Miniature, Compact and Easy for Fabrication. The Miniaturization of this structure is achieved by entering the 'e' slot  in etching area in the ground of CPW line, to save the standard gap of the adapted coplanar line. The designed coplanar LPF is a compact filter having a large band pass and extended stop band, with the possibility to associate easily with others RF and microwave planar circuits. The entire area of the proposed structure of CPW LPF is 14.3x20 mm2.
Quality and texture analysis of biometric images compressed with second-generation wavelet transforms and SPIHT-Z encoder Ahmed Bouida; Mohammed Beladgham; Abdesselam Bassou; Ismahane Benyahia
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1325-1339

Abstract

In biometric systems, compression takes important place especially in order to reduce the size of the information stored or transmitted through the distributed biometric systems. It is also noted that the compression techniques induce loss of information in the compressed images that can affect the effectiveness of biometric systems. The main objective of our contribution is to examine the efficacy of the used method to offer an optimal compression quality in these kind of images without considerable distortion. In order to evaluate the efficacy of the compression process, we use two kinds of evaluation, full-reference image quality assessment and a new proposed textural quality analysis of the compressed images. In this paper, we use a second-generation wavelet transform to improve the compression study in biometric images. The basic idea of this algorithm is the quincunx wavelet transform coupled to a modified progressive encoder called SPIHT-Z encoding.
3D model retrieval using MeshSIFT descriptor and fuzzy C-means clustering Najlaa Abd Hamza; Shatha Habeeb Jafer; Raghad Mohammed Hadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1452-1460

Abstract

A huge number of three-dimensional models exists on the internet, due to the fact that there are now more three-dimensional modelling and digitizing tools available for ever-increasing applications. The procedures for retrieval of three-dimensional models have thus become even more essential. The subject of this paper is a shape retrieval of 3D models that are signified as triangle meshes. We propose a new method which first computes the descriptor of 3D models through extracting its features, and then divides a model into clusters depending on a descriptor which is invariant to scale and orientation. A Fuzzy C-means clustering method is utilized for dividing the model into clusters. The superior performance and benefits of our method are shown in the results.
Automatic segmentation of ceramic materials with relaxed possibilistic C-Means clustering for defect detection Kwang Baek Kim; Doo Heon Song; Hyun Jun Park
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1505-1511

Abstract

Auromatic inspection system is necessary for reliable quality control if ceramic materials to avoid operator subjectivity and fatigue in visual inspection. Automatic segmentation from material’s image is then the most important process to develop such an inspection system. In this paper, we propose a Possibilistic C-Means pixel clustering algorithm with fuzzy stretching to form the defect object in segmentation. In experiment using 50 images containing a certain amount of defects, the proposed method was successful in 49 cases or 98% of opportunities. That performance is roughly twice better than that of standard K-means clustering in defect object formation Auromatic inspection system is necessary for reliable quality control if ceramic materials to avoid operator subjectivity and fatigue in visual inspection. Automatic segmentation from material’s image is then the most important process to develop such an inspection system. In this paper, we propose a Possibilistic C-Means pixel clustering algorithm with fuzzy stretching to form the defect object in segmentation. In experiment using 50 images containing a certain amount of defects, the proposed method was successful in 49 cases or 98% of opportunities. That performance is roughly twice better than that of standard K-means clustering in defect object formation.
On the review of image and video-based depression detection using machine learning Arselan Ashraf; Teddy Surya Gunawan; Bob Subhan Riza; Edy Victor Haryanto; Zuriati Janin
Indonesian Journal of Electrical Engineering and Computer Science Vol 19, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v19.i3.pp1677-1684

Abstract

Machine learning has been introduced in the sphere of the medical field to enhance the accuracy, precision, and analysis of diagnostics while reducing laborious jobs. With the mounting evidence, machine learning has the capability to detect mental distress like depression. Since depression is the most prevalent mental disorder in our society at present, and almost the majority of the population suffers from this issue. Hence there is an extreme need for the depression detection models, which will provide a support system and early detection of depression. This review is based on the image and video-based depression detection model using machine learning techniques. This paper analyses the data acquisition techniques along with their databases. The indicators of depression are also reviewed in this paper. The evaluation of different researches, along with their performance parameters, is summarized. The paper concludes with remarks about the techniques used and the future scope of using the image and video-based depression prediction. 

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