Abstract
This work is aimed to produce a robust thresholding method for segmenting the MRI brain images. A popular thresholding method commonly used in digital image segmentation is the Kittler and Illingworth’s (MET) method because it improves the segmentation process effectively. It is easy to implement and works well with the general images. However, it fails to segment the MRI brain images. This paper proposed a method to modify the objective function of traditional MET method by including the total variance of given image and a weight parameter. This method gives the satisfactory results for the MRI brain images, while compared with other threshold methods and traditional MET method. The segmented images are compared by using the region non–uniformity (NU) parameter. The NU value of proposed work is very low while compared with the original and other existing methods. The MRI brain images are segmented by the proposed work have sub structural clarity for further processing.
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Kalaiselvi, T., Nagaraja, P. (2013). Modified Kittler and Illingworth’s Thresholding for MRI Brain Image Segmentation. In: Prasath, R., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8284. Springer, Cham. https://doi.org/10.1007/978-3-319-03844-5_18
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DOI: https://doi.org/10.1007/978-3-319-03844-5_18
Publisher Name: Springer, Cham
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