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ITS » Undergraduate Theses » Teknik Informatika
Posted by jono at 30/06/2009 14:07:34  •  7308 Views


SISTEM TEMU KEMBALI CITRA BERBASIS ISI MENGGUNAKAN ALGORITMA MARGINAL FISHER ANALYSIS

MARGINAL FISHER ANALYSIS FOR CONTENTBASED IMAGE RETRIEVAL

Author :
Setyaningsih, Intan 




ABSTRAK

Sistem temu kembali citra berbasis isi adalah aplikasi pencarian suatu citra digital pada basis data citra yang berukuran besar dengan menggunakan ukuran kemiripan citra. Algoritma-algoritma reduksi dimensi yang bertujuan untuk memilih himpunan sederhana dari suatu ciri yang efisien dan berbeda memiliki perhatian yang tinggi untuk sistem temu kembali citra berbasis isi. Pada Tugas Akhir ini diterapkan algoritma Marginal Fisher Analysis untuk menyelesaikan permasalahan tersebut. Pada algoritma ini dirancang grafik intrinsik yang menggolongkan kepadatan intra-kelas dan grafik pinalti yang menggolongkan pemisahan antar-kelas. Grafik intrinsik mengilustrasikan relasi adjacent titik-titik intra-kelas dan setiap contoh dihubungkan ke k1- nearest neighbor dalam kelas yang sama. Grafik pinalti mengilustrasikan relasi adjacent titik marginal dan pasanganpasangan titik marginal dari kelas berbeda yang terhubung. Melalui proses uji coba dan evaluasi dapat disimpulkan bahwa Marginal Fisher Analysis terbukti efektif dalam meningkatkan performa sistem. Kinerja pencarian pada sistem yang diimplementasikan memiliki keakuratan yang tinggi sebesar 0.9344 untuk nilai Precision dan Recall yang dihasilkan pada 9 jumlah pencarian citra.


ABSTRACT

Content-based image retrieval was the application of the search for the digital image from the large database by using the measurement of the image resemblance. Dimensionality reduction algorithmswhich aim to select a small set of efficient and discriminant features have attracted great attention for content-based image retrieval CBIR. In this final project we implement marginal Fisher Analysis to address these problems. In this algorithm an intrinsic graph that characterizes the intraclass compactness and another penalty graph which characterizes the interclass separability are designed. The intrinsic graph illustrates the intraclass point adjacency relationship and each sample is connected to its k1- nearest neighbors of the same class. The penalty graph illustrates the interclass marginal point adjacency relationship and the marginal point pairs of different classes are connected. Based on experiments and evaluation it can be concluded that Marginal Fisher Analysis is an efficient method for increasing systems performance. The achievement of the search for 9 image had the high accuration of 0.9344 for the precision and recall value.



KeywordsSistem Temu Kembali Citra Berbasis Isi, reduksi dimensi, Marginal Fisher Analysis.
 
Subject:  Image processing
Contributor
  1. Rully Soelaiman,S.Kom,M.Kom Ahmad Saikhu,S.Si,MT
Date Create: 30/06/2008
Type: Text
Format: pdf
Language: Indonesian
Identifier: ITS-Undergraduate-3100008033774
Collection ID: 3100008033774
Call Number: RSIf 006.42 Set s


Source
DEPARTMENT OF INFORMATICS Faculty Of Information Technology,RSIf 006.42 Set s,2008

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ITS-Undergraduate-3100008033774-4877.pdf




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