GLCM-BasedFeature Extraction for Alpha Matting on Natural Images

GLCM-BasedFeature Extraction for Alpha Matting on Natural Images

mage matting;threshold determination;feature extraction;region of interest and gray-level of co-occurrence matrix

The main objective of this research is to determine the optimal threshold value in the unknown region in the alpha-matting operation of natural images. Alpha-mating serves to draw matte from the image used in segmentation. The alpha value is very influential on the quality of segmentation which is determined by the level of threshold value accuracy. The determination ofthe threshold begins by breaking the grayscale image into several sub-imagesusing Region of Interest (RoI). Each sub-imagewas extracted using the Gray Level Co-occurrence Matrix (GLCM) considered by the parameters of contrast, energy, and entropy at angles of 0°, 45°, 90°, and 135 °. Each feature results in extractions, which are then averaged and normalized in each sub-image. The value is determined as the local threshold value used in the alpha matting operation. Experiments were carried out on 12 natural images from the image-mating dataset to evaluate the performance of the proposed algorithm. The increase in accuracy shows up to 63% by the measurements of experiments, compared to the calculation of adaptive threshold by using the fuzzy CMs Algorithm

Ruri Suko Basuki1*, Jehad A.H Hammad

https://jurnal.iaii.or.id/index.php/RESTI/article/view/5644/943

1Faculty of Computer Science, Department of Informatic Engineering, Dian Nuswantoro University, Indonesia

27-06-2024

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