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REKONSTRUKSI OBYEK TIGA DIMENSI DARI CITRA DUA DIMENSI MENGGUNAKAN EPIPOLAR GEOMETRY Rachmawati, Rachmawati; Hidayat, Risanuri; Wibirama, Sunu
Jurnal Teknologi Vol 5 No 2 (2012): Jurnal Teknologi
Publisher : Jurnal Teknologi, Fakultas Teknologi Industri, Institut Sains & Teknologi AKPRIND Yogyakarta

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Abstract

Teknik rekonstruksi objek tiga dimensi terbagi menjadi 2 kategori, yaitu metode aktif: akuisisi model 3D dapat dilakukan dengan laser scanner atau cahaya terstruktur. Metode pasif : rekonstruksi model 3D dengan sekumpulan gambar dari sebuah atau beberapa kamera. Object scanning terkadang membutuhkan peralatan yang mahal dan keahlian khusus untuk mengoperasikan. Sebagai pendekatan yang sederhana dan murah, rekonstruksi objek berdasarkan gambar menjadi lebih popular bagi para peneliti. Paper ini menjelaskan rekonstruksi obyek tiga dimensi (3D) dari kumpulan gambar citra dua dimensi (2D) yang diambil menggunakan sebuah kamera dari posisi berbeda.Tahapan rekonstruksi dapat dibagi menjadi empat bagian: pertama, ekstraksi titik fitur, kedua menghitung fundamental matrik dari titik – titik yang berkoresponden, ketiga menghitung matrik kamera dan terakhir mendapatkan titik-titik 3D untuk semua pasangan titik citra. Tujuan dari penelitian ini adalah merekonstruksi sebuah obyek 3D menggunakan citra 2D yang diperoleh dengan sebuah kamera dari sudut pandang yang berbeda.Sebagai obyek penelitian adalah sebuah miniatur candi Borobudur.Rekonstruksi koordinat 3D objek candi Borobudur dilakukan dengan algoritma DLT, dan dari hasil rekonstruksi didapat error reproyeksi sebesar 8.864x10-06piksel. Kata kunci :, citra, ,
Virtual Reality-based Platformer Games Development for Elevating Architectural Heritage Awareness Nasikun, Ahmad; Wijonarko, Bagas Y.; Rahman, Raja Bagus Arief; Persada, Anugerah Galang; Wibirama, Sunu
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 1, No 3 (2017): September 2017
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (998.169 KB) | DOI: 10.22146/ijitee.33592

Abstract

As a country with abundant traditional culture, Indonesia is facing serious challenge in conserving them. There is a need to promote the traditional culture to a wider area of people, particularly to the younger generation. Virtual world offers a new way of promoting a nation’s culture via Virtual Reality (VR). This research aims to develop a VR-based platformer mobile game to promote cultural awareness in a new and creative way for younger generation. In the game, a player can observe one famous architectural heritage in Yogyakarta—Mesjid Gedhe Kauman—in fun way of game. A survey is conducted to measure its success in reaching the predetermined goals and to measure its user experience (UX). The survey confirm that the VR-based platformer game helps them in learning cultural value of the architecture (62.5/100) and it is relatively easy to navigate (72.5/100). Moreover, it has a good user experience (UX) score—all are above 0.8, meaning that its users are generally comfortable in playing the game.
Analysis of Segmentation Parameters Effect towards Parallel Processing Time on Fuzzy C Means Algorithm Ramdani, Cepi; Soesanti, Indah; Wibirama, Sunu
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 1, No 4 (2017): December 2017
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1362.623 KB) | DOI: 10.22146/ijitee.35025

Abstract

Fuzzy C Means algorithm or FCM is one of many clustering algorithms that has better accuracy to solve problems related to segmentation. Its application is almost in every aspects of life and many disciplines of science. However, this algorithm has some shortcomings, one of them is the large amount of processing time consumption. This research conducted mainly to do an analysis about the effect of segmentation parameters towards processing time in sequential and parallel. The other goal is to reduce the processing time of segmentation process using parallel approach. Parallel processing applied on Nvidia GeForce GT540M GPU using CUDA v8.0 framework. The experiment conducted on natural RGB color image sized 256x256 and 512x512. The settings of segmentation parameter values were done as follows, weight in range (2-3), number of iteration (50-150), number of cluster (2-8), and error tolerance or epsilon (0.1 – 1e-06). The results obtained by this research as follows, parallel processing time is faster 4.5 times than sequential time with similarity level of image segmentations generated both of processing types is 100%. The influence of segmentation parameter values towards processing times in sequential and parallel can be concluded as follows, the greater value of weight parameter then the sequential processing time becomes short, however it has no effects on parallel processing time. For iteration and cluster parameters, the greater their values will make processing time consuming in sequential and parallel become large. Meanwhile the epsilon parameter has no effect or has an unpredictable tendency on both of processing time.
Prototype of Student Attendance Application Based on Face Recognition Using Eigenface Algorithm Prabowo, Tio Eko; Hartanto, Rudy; Wibirama, Sunu
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 3, No 1 (2019): March 2019
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1047.999 KB) | DOI: 10.22146/ijitee.46724

Abstract

Prototype of face recognition based attendance application that has been developed to overcome weaknesses in DTETI UGM student manual attendance system has several weaknesses. These weaknesses are a decrease in facial recognition accuracy when operating under conditions of varying environmental light intensity and in condition of face rotating towards z axis rotation centre. In addition, application prototype also does not yet have a database to store attendance results. In this paper, a new application prototype has been developed using Eigenface face detection and recognition algorithm and Haar-based Cascade Classifier. Meanwhile, to overcome prototype performance weaknesses of the previously developed application, a pre-processing method was proposed in another study was added. Processes in the method were geometry transformation, histogram levelling separately, image smoothing using bilateral filtering, and elliptical masking. The test results showed that in the category of various environmental light intensity conditions, face recognition accuracy from developed application prototypes was 16.71% better than previous application prototypes. Meanwhile, in category of face slope conditions at z axis rotation centre, face recognition accuracy from developed application prototype was 38.47% better. Attendance database system was also successfully implemented and running without error.
Eye Blink Classification for Assisting Disability to Communicate Using Bagging and Boosting Ardi, Luthfi; Setiawan, Noor Akhmad; Wibirama, Sunu
IJITEE (International Journal of Information Technology and Electrical Engineering) Vol 5, No 4 (2021): December 2021
Publisher : Department of Electrical Engineering and Information Technology,Faculty of Engineering UGM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijitee.63515

Abstract

Disability is a physical or mental impairment. People with disability have more barriers to do certain activity than those without disability. Moreover, several conditions make them having difficulty to communicate with other people. Currently, researchers have helped people with disabilities by developing brain-computer interface (BCI) technology, which uses artifact on electroencephalograph (EEG) as a communication tool using blinks. Research on eye blinks has only focused on the threshold and peak amplitude, while the difference in how many blinks can be detected using peak amplitude has not been the focus yet. This study used primary data taken using a Muse headband on 15 subjects. This data was used as a dataset classified using bagging (random forest) and boosting (XGBoost) methods with python; 80% of the data was allocated for learning and 20% was for testing. The classified data was divided into ten times of testing, which were then averaged. The number of eye blinks’ classification results showed that the accuracy value using random forest was 77.55%, and the accuracy result with the XGBoost method was 90.39%. The result suggests that the experimental model is successful and can be used as a reference for making applications that help people to communicate by differentiating the number of eye blinks. This research focused on developing the number of eye blinks. However, in this study, only three blinking were used so that further research could increase these number.