Performance of Median Filter and its Variants for the Preprocessing of Mammilla Cancer Imagery
Madhukar. B. N.1, Bharathi. S. H.2, G. T. Raju3, Chetan T. Madiwalar4, Sachin Munji5

1Mr. Madhukar. B. N., Pursuing Ph.D, School of ECE, REVA University, Bengaluru (Karnataka), India.

2Dr. Bharathi. S. H., Professor, School of ECE, REVA University, Bengaluru (Karnataka), India.

3Dr. G. T. Raju, HOD, Department of CSE, RNS Institute of Technology, Bengaluru (Karnataka), India.

4Mr. Chetan T. Madiwalar, Department of Electronics and Communication Engineering, Manipal University, (Karnataka), India.

5Mr. Sachin Munj, Department of Electronics and Communication Engineering, VTU, Belgaum (Karnataka), India.

Manuscript received on 07 December 2019 | Revised Manuscript received on 15 December 2019 | Manuscript Published on 31 December 2019 | PP: 605-610 | Volume-9 Issue-2S December 2019 | Retrieval Number: B10601292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1060.1292S19

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper presents a comparison of the Median Filter and its variants that are used for the preprocessing of mammilla cancer images in Medical Imaging. Preprocessing of mammilla cancer images is a very important step in their accurate espial. Median filters and its other versions such as Adaptive Median Filter, Progressive Switching Median Filter, and Relaxed Median Filter are applied on a dataset of open source mammilla cancer images for their preprocessing. Their perpetration is compared based on various performance metrics and it’s inferred that the Relaxed Median Filter outperforms the performance of the other Median Filters used.

Keywords: Median, Adaptive, Filter, Switching.
Scope of the Article: Measurement & Performance Analysis