Abstract
Since the invention of computers, image processing methods have been utilized in a variety of applications, where their significance has grown. An important topic and the main emphasis of image processing methods are image segmentation, which is also a classic topic in the area. In order to segment images, a number of general-purpose algorithms and methods have been created. Since the image segmentation problem does not have a generic solution, these strategies frequently need to be paired with domain expertise to successfully solve an image segmentation problem for a problem domain. In this paper, we present a comparative study of basic two types of fuzzy convergence with a midpoint as image segmentation techniques.
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The researchers thankfully acknowledge the reviewers for the beneficial comments.
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Alameen, H.A., Kareem, N.R., Habeeb, S.Q. (2023). Fuzzy Net for Image Processing Applications: Image Segmentation. In: Sharma, D.K., Peng, SL., Sharma, R., Jeon, G. (eds) Micro-Electronics and Telecommunication Engineering . Lecture Notes in Networks and Systems, vol 617. Springer, Singapore. https://doi.org/10.1007/978-981-19-9512-5_56
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DOI: https://doi.org/10.1007/978-981-19-9512-5_56
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