Comparative Study of Image Segmentation using Variants of Self Organizing Maps (SOM)
نویسندگان
چکیده
Image segmentation is a very crucial step in the field of image processing which helps us to simplify the representation of the image, to make it easier to analyze. This paper deals with the comparison of image segmentation techniques based on unsupervised artificial neural network technique, known as Kohonen’s Self Organizing Maps (SOM). We first present image segmentation using Kohonen’s Self Organizing Map. Secondly, we focus on the Threshold Self Organizing Map (TSOM) and finally multilevel Self Organizing Maps. We then evaluate each of the outputs based on different image segmentation parameters. Finally, we compare the parameters of each output and present our conclusion.
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