Azmi Tawfik Alrawi, Ali makki Sagheer and Dheyaa Ahmed Ibrahim, University of Anbar, Iraq
ABSTRACT
Texture segmentation can be considered the most important problem, since human can distinguish different textures quit easily, but the automatic segmentation is quit complex and it is still an open problem for research. In this paper focus on implement novel supervised algorithm for multitexture segmentation and this algorithm based on blocking procedure where each image divide into block (16×16 pixels) and extract vector feature for each block to classification these block based on these feature. These feature extract using Box Counting Method (BCM). BCM generate single feature for each block and this feature not enough to characterize each block ,therefore, must be implement algorithm provide more than one slide for the image based on new method produce multithresolding, after this use BCM to generate single feature for each slide.
KEYWORDS
Texture Segmentation; MultifractalDiension; Fractal Dimension; Box Counting
Original Source URL: http://airccse.org/journal/ijsc/papers/2112ijsc01.pdf
https://airccse.org/journal/ijsc/current2012.html
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#texturesegmentation #multifractional #boxcounting #softcomputing
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