ANALISIS TEKSTUR PHOTO LAMA MENGGUNAKAN FITUR TEKSTUR GRAY LEVEL CO-OCCURRENCE MATRIKS PADA PEWARNAAN CITRA OTOMATIS
DOI:
https://doi.org/10.26623/elektrika.v10i1.1160Keywords:
Texture, Glcm, MAE, MSEAbstract
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
Downloads
References
. Ambika Kalia1, Balwinder Singh, Colorization of Grayscale Images: An Overview , ournal of Global Research in Computer Science, Volume 2, No. 8, August 2011 [2]. R. Venkata Rahmana Chary, D. Rajya Laksmi, K.V.N. Sunitha. Feature extraction methods for color image similarity . Institute of Technology, India, 2012. [3]. Shiguang liu, Xhiang Zhang, Automatic Grayscale image colorasion using histogram regression , School of computer science and technology, Tianjin University, china, 2012.
. 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.
Downloads
Published
Issue
Section
License
Authors who publish this journal agree to the following terms:
The author owns the copyright and grants the journal the first publication rights with the work simultaneously licensed under the Creative Commons Attribution 4.0 International License which allows others to share the work with recognition of the authorship of the work and initial publication in the journal.
Authors may enter into separate additional contractual agreements for non-exclusive distribution of the published journal version of the work (e.g., posting it to an institutional repository or publishing it in a book), in recognition of its initial publication in this journal.
Authors are allowed and encouraged to post their work online (e.g., in institutional repositories or on their websites) before and during the submission process, as it can lead to productive exchanges, as well as earlier and larger citations of published works (See The Effects of Open Access).
This work is licensed under the Creative Commons Attribution 4.0 International License.