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All Journal Jurnal Teknik Elektro TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Techne : Jurnal Ilmiah Elektroteknika Jurnal Litbang Provinsi Jawa Tengah Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat
Darmawan Utomo
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences

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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

 1 
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 Aaron Berliano Handoko Acip Susman Alyahi Adi Wicitra Atyanta Nika Rumaksari Banu Wirawan Yohanes Budhi Kurniawan Wangsa Budihardja Murtianta Christian Nugraha Deddy Susilo Donny K. Sutantyo Fransiscus Dalu Setiaji Handoko Handoko Hartanto Kusuma Wardana Ignatius Prima H. Prabowo Indria Prambodo, Natanael Ivanna Kristianti Timotius Jati Kristianto Johny Salim Kevin Murtianta, Budihardja Ricky Jeconiah Samuel Aditya Utomo Samuel Alvin Hutama Sandro Angkat Saptadi Nugroho Vinsensius R.S. Purnomo