Friday 29th of March 2024
 

The Use of Self Organizing Map Method and Feature Selection in Image Database Classification System


Dian Pratiwi

This paper presents a technique in classifying the images into a number of classes or clusters desired by means of Self Organizing Map (SOM) Artificial Neural Network method. A number of 250 color images to be classified as previously done some processing, such as RGB to grayscale color conversion, color histogram, feature vector selection, and then classifying by the SOM Feature vector selection in this paper will use two methods, namely by PCA (Principal Component Analysis) and LSA (Latent Semantic Analysis) in which each of these methods would have taken the characteristic vector of 50, 100, and 150 from 256 initial feature vector into the process of color histogram. Then the selection will be processed into the SOM network to be classified into five classes using a learning rate of 0.5 and calculated accuracy. Classification of some of the test results showed that the highest percentage of accuracy obtained when using PCA and the selection of 100 feature vector that is equal to 88%, compared to when using LSA selection that only 74%. Thus it can be concluded that the method fits the PCA feature selection methods are applied in conjunction with SOM and has an accuracy rate better than the LSA feature selection methods.

Keywords: Color Histogram, Feature Selection, LSA, PCA, SOM.

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ABOUT THE AUTHOR

Dian Pratiwi
) was born in Jakarta – Indonesia on February 25, 1986. The last education is The Master of Information Technology achieved in 2011 at The University of Bina Nusantara, Jakarta – Indonesia with a GPA of 3,66. Her bachelor achieved at Trisakti University, Jakarta – Indonesia with the title of “Very Satisfied” and was awarded as “One of The 7 Best Graduate Department of Information Engineering” in 2007. Now, the author worked as a lecturer at Trisakti University also taught courses in image processing, mobile programming, web based programming, and computer graphics began in 2008 until now. Some writings ever made that has been published is entitled “An Application of Backpropagation Artificial Neural Network Method for Measuring The Severity of Osteoarthritis”, which in 2011 published in the journal IJENS – IJET. In addition, the author also wrote another article which successfully published nationally in Indonesia at the SNTI seminar : (Jakarta, Indonesia : Trisakti University, 2010) with the title “Sistem Deteksi Penyakit Pengeroposan Tulang dengan Metode Jaringan Syaraf Tiruan Backpropagation dan Representasi Ciri dalam Ruang Eigen” and SITIA seminar (Surabaya, Indonesia : Institute of Ten November Technology – ITS, 2011) entitled “Penerapan Metode Jaringan Syaraf Tiruan Backpropagation dalam Mengukur Tingkat Keparahan Penyakit Osteoarthritis” which results in the proceedings. Now, she keep trying to develop her research on the medical by trying to apply her research interests are in Artificial Intelligence, digital image processing, and data mining.


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