E - Conference Unversitas Merdeka Malang

View Publication Info
Field Value
Creator Handi Rahmannuri; Akademi Komunitas Semen Indonesia (AKSI) Gresik
Subject Rekayasa dan teknologi Informasi
Identifikasi, intensitas pencahayaan, objek gerak, computer vision
Description AbstrakTujuan penelitian ini adalah memperoleh informasi pengaruh perbedaan intensitas pencahayaan (rendah, sedang, dan tinggi) terhadap kemampuan identifikasi objek gerak. Dengan dasar tujuan tersebut, penelitian ini diharapkan menghasilkan rekomendasi dalam bentuk data dan teori yang menunjang algoritma dan komputasi sistem computer vision yang berfungsi untuk mengidentifikasi objek gerak di lingkungan yang dinamis yang lebih akurat dan handal. Hasil penelitian ini nantinya akan digunakan sebagai pedoman standar peneliti yang bergelut di bidang computer vision, khususnya identifikasi objek gerak. Sistem Deteksi objek gerak dalam penelitian ini menggunakan perangkat lunak Microsoft Visual Studio dengan penggunakan bahasa pemrograman C++ dan kamera PSEye. Objek gerak diidentifikasi dengan jarak ±100 cm dari kamera. Kemampuan identifikasi objek mengalami perubahan ketika intensitas cahaya sekitar berubah. Pada intensitas cahaya 78 lux kemampuan identifikasi objek lingkaran menunjukkan proses identifikasi sebanyak 31 kali selama 15 detik, pada intensitas cahaya 121 lux kemampuan identifikasi objek lingkaran menunjukkan proses identifikasi sebanyak 8 kali selama 15 detik, dan pada intensitas cahaya 278 lux kemampuan identifikasi objek lingkaran dapat mengunci target secara sempurna selama 15 detik.  AbstractThe purpose of this study was to obtain information on the effect of differences in lighting intensity (low, medium, and high) on the ability of identification of moving objects. On the basis of these objectives, this research is expected to produce recommendations in the form of data and theories that support algorithms and computational computer vision systems that serve to identify moving objects in dynamic environments that are more accurate and reliable. The results of this study will be used as a standard guideline for researchers who are engaged in the field of computer vision, specifically identification of moving objects. The moving object detection system in this study uses Microsoft Visual Studio software using the C ++ programming language and PSEye camera. The moving object is identified with a distance of ± 100 cm from the camera. The ability to identify objects changes when the intensity of ambient light changes. At light intensity 78 lux circle object identification ability shows identification process as many as 31 times for 15 seconds, at light intensity 121 lux circle object identification ability shows identification process as much as 8 times for 15 seconds, and at light intensity 278 lux ability to identify circle objects can lock the target perfectly for 15 seconds.
Publisher Seminar Nasional Sistem Informasi
Date 2019-09-02 06:22:26
Type Peer-reviewed Paper

Source Seminar Nasional Sistem Informasi; SEMINAR NASIONAL SISTEM INFORMASI (SENASIF) 2019
Language en

Rights Authors who submit to this conference agree to the following terms:<br /> <strong>a)</strong> Authors retain copyright over their work, while allowing the conference to place this unpublished work under a <a href="">Creative Commons Attribution License</a>, which allows others to freely access, use, and share the work, with an acknowledgement of the work's authorship and its initial presentation at this conference.<br /> <strong>b)</strong> Authors are able to waive the terms of the CC license and enter into separate, additional contractual arrangements for the non-exclusive distribution and subsequent publication of this work (e.g., publish a revised version in a journal, post it to an institutional repository or publish it in a book), with an acknowledgement of its initial presentation at this conference.<br /> <strong>c)</strong> In addition, authors are encouraged to post and share their work online (e.g., in institutional repositories or on their website) at any point before and after the conference.

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us


Copyright © 2015-2018 Simon Fraser University Library