A Type-2 Fuzzy in image extraction for DICOM image

19Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.

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.

Cite

CITATION STYLE

APA

Nagarajan, D., Lathamaheswari, M., Kavikumar, J., & Hamzha. (2018). A Type-2 Fuzzy in image extraction for DICOM image. International Journal of Advanced Computer Science and Applications, 9(12), 351–362. https://doi.org/10.14569/ijacsa.2018.091251

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free