Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras

  • Bheta Agus Wardijono STMIK Jakarta STI&K
  • Lussiana ETP STMIK Jakarta STI&K
  • Rozi STMIK Jakarta STI&K
Keywords: image edge detection, image characteristics, regionization, entropy, contrast.

Abstract

Abstract

Determining the object boundaries in an image is a necessary process, to identify the boundaries of an object with other objects as well as to define an object in the image. The acquired image is not always in good condition, on the other hand there is a lot of noise and blur. Various edge detection methods have been developed by providing noise parameters to reduce noise, and adding a blur parameter but because these parameters apply to the entire image, but lossing some edges due to these parameters. This study aims to identify the characteristics of the image region, whether the region condition is noise, blurry or otherwise sharp (clear). The step is done by dividing the four regions from the image size, then calculating the entropy value and contrast value of each formed region. The test results show that changes in region size can produce different characteristics, this is indicated by entropy and contrast values ​​of each formed region. Thus it can be concluded that entropy and contrast can be used as a way to identify image characteristics, and dividing the image into regions provides more detailed image characteristics.

 

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References

E. Bourennane, P. Gouton, M. Paindavoine, F. Truchetet, ”Generalization Of Canny – Deriche Filter For Detection Of Noisy Exponential Edge”, Signal Processing, vol. 82, no. 10, pp. 1317–1328, 2002.

P. Zhou, Ye, W., & Wang, Q., ”An Improved Canny Algorithm for Edge Detection”, Journal of Computational Information Systems, vol. 7, no. 5, pp. 1516-1523, 2011.

C. Bustacara-Medina, Leonardo Florez-Valencia, Luis Carlos Diaz, ”Improved Canny Edge Detector Using Principal Curvatures”, Journal of Electrical and Electronic Engineering. vol. 8, no. 4, pp. 109-116, 2020.

J. Canny, ”A Computational Approach To Edge Detection”, IEEE on Pattern Analysis and Machine Intelligence. vol. 8, pp. 679-698, 1986.

G. Farnebäck, and Carl-Fredrik Westin, 2006. ”Improving Deriche-style Recursive Gaussian Filters”, Journal of Mathematical Imaging and Vision. vol. 26. pp. 293-299, 2006.

R. Deriche, ”Using Canny’s Criteria To Derive A Recursively Implemented Optimal Edge Detector”, Computer Vision, vol. 1, no. 2, pp. 167-187, 1987.

R.C. Gonzalez, R.E.Woods, dan S.L. Eddins, Digital Image Processing using MATLAB. Pearson Education, 2004.

P. Gouton, Hayet Laggoune, R. K. Kouassi, and Michel Paindavoine, ”Ridge-line optimal detector”, Optical Engineering, vol. 39, no. 6, pp. 1602-1611, 2000.

M. Lievin, F. Luthon, E. Keeve, ”Entropic Estimation of Noise for Medical Volume Restoration”, International Conference on Pattern Recognition, vol 3, pp. 30871, 2002.

S. Pyatykh, Hesser J, Zheng L, ”Image noise level estimation by principal component analysis”. IEEE Trans Image Process, vol. 22, no. 2, pp.687-699, 2013.

P. Fu, Changyang Li, Yong Xia, Zexuan Ji, Quansen Sun, Weidong Cai, David Dagan Feng, ”Adaptive noise estimation from highly textured hyperspectral images”, Appl. Opt. Vol.53, no.30, pp.7059-7071, October 2014.

S. Madenda, R. Missaoui, J. Vaillancourt and M. Paindavoine, ”An Enhanced Detector of Blurred and Noisy Edges”, Signal Processing for Image Enhancement and Multimedia Processing, pp. 127‐140, 2008.

R. Munir, 2004. Pengolahan Citra Digital dengan Pendekatan Algoritmik. Penerbit Informatika Bandung.

R. Dorothy, R.M. Joany, R. Joseph Rathish, S. Prabha, S. Rajendran, ”Image enhancement by Histogram Equalization”, International Journal of Nano Corrosion Science and Engineering, vol. 2, pp. 21-30, 2015.

H. Budi, dan Veronica Lusiana, ”Analisa Teknik Adaptive Histogram Equalization dan Contrast Stretching untuk Perbaikan Kualitas Citra”, Jurnal Teknologi Informasi Dinamik, vol. 19, no. 1, pp 1-10, 2014.

Published
2021-06-02
How to Cite
[1]
B. A. Wardijono, Lussiana ETP, and Rozi, “Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras”, JACOST, vol. 2, no. 1, pp. 18 - 23, Jun. 2021.
Section
Articles
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