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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Teknik dan Ilmu Komputer Techne : Jurnal Ilmiah Elektroteknika Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Saptadi Nugroho
Universitas Kristen Satya Wacana
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

 1 
Location and Position Determination Algorithm For Humanoid Soccer Robot Oei Kurniawan Utomo; Daniel Santoso; Saptadi Nugroho
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2710

Abstract

The algorithm of location and position determination was designed for humanoid soccer robot. The robots have to be able to control the ball effectively on the field of Indonesian Robot Soccer Competition which has a size of 900 cm x 600 cm. The algorithm of location and position determination uses parameters, such as the goalpost’s thickness, the compass value, and the robot’s head servo value. The goalpost’s thickness is detected using The Centre of Gravity method. The width of the goalpost detected is analyzed using the principles of camera geometry to determine the distance between the robot and the goalpost. The tangent value of head servo’s tilt angle is used to determine the distance between the robot and the ball. The distance between robot-goalpost and the distance between robot-ball are processed with the difference of head servo’s pan angle and compass value using trigonometric formulas to determine the coordinates of the robot and the ball in the Cartesian coordinates.
Rotation Invariant Indexing For Image Using Zernike Moments and R–Tree Saptadi Nugroho; Darmawan Utomo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 9, No 2: August 2011
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v9i2.705

Abstract

The Zernike moment algorithm and R-Tree algorithm are known as state of the art in the recognition of images and in the multimedia database respectively. The methods of storing the images and retrieving the similar images based on a query image automatically are the problems in the image database. This paper proposes the method to combine the Zernike moments algorithm and the R–tree algorithm in the image database. The indices of images which are retrieved from the extraction process using Zernike moments algorithm are used as the multidimensional indices to recognize the images. The multidimensional indices of Zernike moments which are stored in the R–tree are compared to the magnitudes of Zernike moments of a query image for searching the similar images. The result shows that the combination of these algorithms can be used efficiently in the image database because the recognition accuracy rate using Zernike moments algorithm is 95.20%.
Features Deletion on Multiple Objects Recognition using Speeded-Up Robust Features, Scale Invariant Feature Transform and Randomized KD-Tree Samuel Alvin Hutama; Saptadi Nugroho; Darmawan Utomo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 2: June 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i2.3461

Abstract

This paper presents a multiple objects recognition method using speeded-up robust features (SURF) and scale invariant feature transform (SIFT) algorithm. Both algorithms are used for finding features by detecting keypoints and extracting descriptors on every object. The randomized KD-Tree algorithm is then used for matching those descriptors. The proposed method is deletion of certain features after an object has been registered and repetition of successful recognition. The method is expected to recognize all of the registered objects which are shown in an image. A series of tests is done in order to understand the characteristic of the recognizable object and the method capability to do the recognition. The test results show the accuracy of the proposed method is 97% using SURF and 88.7% using SIFT.
Co-Authors Acip Susman Alyahi Aditya Nugraha Tama Aletheia Anggelia Tonoro Banu Wirawan Yohanes Budhi Kurniawan Wangsa Christian Nugraha Daniel Santoso Darmawan Utomo Fandy Oktavianus Suryanputra Hartanto K. Wardana Hartanto Kusuma Wardana Heri Setiawan Ignatius Prima H. Prabowo Iwan Setyawan Jati Kristianto Joshua Marthen Manuputty Oei Kurniawan Utomo Ricky Jeconiah Robert, Teofilus Samuel Alvin Hutama Sanjaya, Kurnia Santoso, Yonathan Darwinto Teofilus Robert Wisnu Jati Rogo Juni