A Type-2 Fuzzy in Image Extraction for DICOM Image

Abstract

Eradication of a desired portion of an image is a very important role in image processing and is also called feature extraction. This is mainly concern about reducing the number of possessions required to portray a large set of data and also reduce memory space requirement and power of data processing. Perfectly optimized feature extraction is an essential process for an effective design construction. Though there are many tools are available for extracting a feature, Type-2 Fuzzy Logic plays a vital role in producing good results. In this paper, weighted arithmetic operator is proposed using Yager triangular norms and proved the properties of the triangular norms using proposed operator. Also, the paper relates the properties to feature extraction. Also Brain has been extracted from patient MRI DICOM image using MATLAB based on Type-2 Fuzzy setting.

Authors and Affiliations

D. Nagarajan, M. Lathamaheswari, J. Kavikumar, Hamzha Hamzha

Keywords

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  • EP ID EP429203
  • DOI 10.14569/IJACSA.2018.091251
  • Views 74
  • Downloads 0

How To Cite

D. Nagarajan, M. Lathamaheswari, J. Kavikumar, Hamzha Hamzha (2018). A Type-2 Fuzzy in Image Extraction for DICOM Image. International Journal of Advanced Computer Science & Applications, 9(12), 351-362. https://europub.co.uk/articles/-A-429203