Image Segmentation using Various Approaches
نویسندگان
چکیده
منابع مشابه
Unsupervised Texture Image Segmentation Using MRFEM Framework
Texture image analysis is one of the most important working realms of image processing in medical sciences and industry. Up to present, different approaches have been proposed for segmentation of texture images. In this paper, we offered unsupervised texture image segmentation based on Markov Random Field (MRF) model. First, we used Gabor filter with different parameters’ (frequency, orientatio...
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Texture image analysis is one of the most important working realms of image processing in medical sciences and industry. Up to present, different approaches have been proposed for segmentation of texture images. In this paper, we offered unsupervised texture image segmentation based on Markov Random Field (MRF) model. First, we used Gabor filter with different parameters’ (frequency, orientatio...
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Abstract: Stochastic models such as mixture models, graphical models, Markov random fields and hidden Markov models have key role in probabilistic data analysis. In this paper, we used Gaussian mixture model to the pixels of an image. The parameters of the model were estimated by EM-algorithm. In addition pixel labeling corresponded to each pixel of true image was made by Bayes rule. In fact,...
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Article history: Received 28 January 2015 Accepted 25 February 2015 Available online 6 March 2015
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ژورنال
عنوان ژورنال: International Journal of Image Processing and Vision Science
سال: 2013
ISSN: 2278-1110
DOI: 10.47893/ijipvs.2013.1074