### ANALISIS TRANSFORMASI BALIK CITRA IRIS MENGGUNAKAN WAVELET HAAR BERDASARKAN FAKTOR RETENSI KOEFISIEN WAVELET

*Agung Wicaksono -  Jurusan Teknik Elektro Fakultas Teknik – Universitas Diponegoro Jl. Prof. Sudharto, SH – Tembalang, Semarang Jawa Tengah 50275, Indonesia
R. Rizal Isnanto -  Jurusan Teknik Elektro Fakultas Teknik – Universitas Diponegoro Jl. Prof. Sudharto, SH – Tembalang, Semarang Jawa Tengah 50275, Indonesia
Achmad Hidayatno -  Jurusan Teknik Elektro Fakultas Teknik – Universitas Diponegoro Jl. Prof. Sudharto, SH – Tembalang, Semarang Jawa Tengah 50275, Indonesia
Diterbitkan: 6 Peb 2013. Citation Format:
Article Info
Bagian: Artikel Jurnal
Bahasa: EN
Teks Lengkap:
Statistik: 137 504
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Abstract

Wavelet is one method that can be used as a step to recognition an individual. Wavelet is used to perform an image feature extraction. In the process of image texture analysis, showed the value of the coefficients of a wavelet. The magnitude of the coefficients obtained using wavelet feature extraction is influenced by several factors. Besides affected by the type of wavelet used, is also influenced by the magnitude of the wavelet decomposition level of itself. In the wavelet is known as the wavelet energy retention, which means the number of retained energy after undergoing a process of decomposition and cutting coefficients. During the decomposition process, the calculation for texture analysis is often a constraint. In order for the current calculation lighter texture analysis, necessary to the process of cutting coefficients based on the retention factor of the wavelet coefficients. Based on these issues, created a program to analyze the influence of variations in the level of wavelet decomposition and coefficient of variation coefficient of cutting a cut on the image. The object of this final project is 30 iris image that has been converted into polar form presented. Having experienced the process of cutting coefficients, to prevent the image of the reverse transformation has a big difference to the original image, in this study was calculated Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), and Euclidean distance to determine the level of similarity of image input and output images. The Highest values of Retention​, MSE and the Euclidean distance is obtained at the level of decomposition of 1 and the lowest at the level of decomposition 6. While the truncated coefficient and PSNR values ​​obtained at the highest level of decomposition of 6 and the lowest level of decomposition of 6. The variation coefficient of pieces, value retention and highest PSNR obtained at koefsien piece 5 and the lowest coefficient of 50 pieces. While the coefficient value is truncated, MSE and the highest Euclidean distance is obtained at koefsien pieces 50 and the lowest coefficient of 5 pieces.

Keywords: iris, texture analysis, Haar wavelet transform, MSE, PSNR, Euclidean distance

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