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Band Segmentation and Detection of DNA by Using Fast Fuzzy C-mean and Neuro Adaptive Fuzzy Inference System

  • Muhammad Arif
  • Guojun WangEmail author
  • Valentina Emilia Balas
  • Shuhong Chen
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1122)

Abstract

Currently, band segmentation is used in medical science, because it helps the scientist to detect and calculate the band and line respectively. Segmentation is very important in medical images, because it provides the clinical assistance to physician. Such as, the DNA images are used to detect and segment the bands and line and calculate the local minima and maxima. For segmentation, we use Fast Fuzzy C-Mean Clustering (FFCM). FFCM is a clustering method that allows a piece of data to be in two or more clusters. Clustering involves the task of dividing the data points into homogeneous classes or the clusters, so that items in the same class are as equitable as possible and the items in the different classes are different. Our results indicate that our proposed method effectively detects the band and counts the lines.

Keywords

DNA Band Segmentation Clustering ANFIS Detection 

Notes

Acknowledgments

This work was supported in part by the National Natural Science Foundation of China under Grant 61632009, in part by the Guangdong Provincial Natural Science Foundation under Grant 2017A030308006, and in part by the High-Level Talents Program of Higher Education in Guangdong Province under Grant 2016ZJ01.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.School of Computer ScienceGuangzhou UniversityGuangzhouChina
  2. 2.Aurel Vlaicu University of AradAradRomania

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