ANALISIS TEKSTUR PHOTO LAMA MENGGUNAKAN FITUR TEKSTUR GRAY LEVEL CO-OCCURRENCE MATRIKS PADA PEWARNAAN CITRA OTOMATIS

Muhammad Sipan, Rony Kartika Pramuyanti

Abstract


 Image processing is important in a process of introduction, classification or segmentation or other processes. One thing that can be done is an analysis of the texture features related to old photos in this case grayscale photos. The object of the research can be an old photo (image) and use a statistical method based on Gray Level Counseling Matrix (GLCM). GLCM is one of the methods used for extracting texture features, some of which are analyzed using glcm by comparing the GLCM texture feature in the old photo with the original photo The coloring process is to provide more visualization of an object, it can be a monochrome image or video with the aim of providing details and clarity of the colored image or video. The study discusses grayscale images to be colored, then searches for GLCM texture feature values. The size of the features obtained from the calculation is used to find out how much the error value indirectly shows how much the image is similar. The measurement of the success of the small scale using the method of Mean Square Error (MSE) and Mean Absolute Error (MAE).

Keyword: Texture, Glcm, MAE, MSE 


Keywords


Texture, Glcm, MAE, MSE

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References


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. V. konusin, V. vezhnevets, “interactive image colorization and recoloring base on coupled map lattices”. Moscow State University, Rusia. [5]. Zhong Zhen, qquad Gui Yan, qquad Ma Lizhuang,” An Automatic Image and Video Colorization Algorithm based on Pattern Continuity”, Shanghai Jiao Tong University, 2012. [6]. Ustin Sousa, Rasoul Kabirzadeh, Patrick Blaes, “Automatic Colorization of Grayscale Images”, Department of Electrical Engineering, Stanford University, 2013.




DOI: http://dx.doi.org/10.26623/elektrika.v10i1.1160

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