An improved Chebyshev distance metric for clustering medical images
A metric or distance function is a function which defines a distance between elements of a set. In clustering, measuring the similarity between objects has become an important issue. In practice, there are various similarity measures used and this includes the Euclidean, Manhattan and Minkowski.In t...
| Main Authors: | , |
|---|---|
| Format: | Conference or Workshop Item |
| Published: |
IP Publishing LLC
2015
|
| Subjects: |
| _version_ | 1803627941761908736 |
|---|---|
| author | Mousa, Aseel Yusof, Yuhanis |
| author_facet | Mousa, Aseel Yusof, Yuhanis |
| author_sort | Mousa, Aseel |
| collection | UUM |
| description | A metric or distance function is a function which defines a distance between elements of a set. In clustering, measuring the similarity between objects has become an important issue. In practice, there are various similarity measures used and this includes the Euclidean, Manhattan and Minkowski.In this paper, an improved Chebyshev similarity measure is introduced to replace existing metrics (such as Euclidean and standard Chebyshev) in clustering analysis.The proposed measure is later realized in analyzing blood cancer images. Results demonstrate that the proposed measure produces the smallest objective function value and converge at the lowest number of iteration.Hence, it can be concluded that the proposed distance metric contribute in producing better clusters. |
| first_indexed | 2024-07-04T06:14:04Z |
| format | Conference or Workshop Item |
| id | uum-20648 |
| institution | Universiti Utara Malaysia |
| last_indexed | 2024-07-04T06:14:04Z |
| publishDate | 2015 |
| publisher | IP Publishing LLC |
| record_format | dspace |
| spelling | uum-206482017-01-18T03:48:08Z https://repo.uum.edu.my/id/eprint/20648/ An improved Chebyshev distance metric for clustering medical images Mousa, Aseel Yusof, Yuhanis QA75 Electronic computers. Computer science A metric or distance function is a function which defines a distance between elements of a set. In clustering, measuring the similarity between objects has become an important issue. In practice, there are various similarity measures used and this includes the Euclidean, Manhattan and Minkowski.In this paper, an improved Chebyshev similarity measure is introduced to replace existing metrics (such as Euclidean and standard Chebyshev) in clustering analysis.The proposed measure is later realized in analyzing blood cancer images. Results demonstrate that the proposed measure produces the smallest objective function value and converge at the lowest number of iteration.Hence, it can be concluded that the proposed distance metric contribute in producing better clusters. IP Publishing LLC 2015 Conference or Workshop Item PeerReviewed Mousa, Aseel and Yusof, Yuhanis (2015) An improved Chebyshev distance metric for clustering medical images. In: 2nd Innovation and Analytics Conference & Exhibition (IACE 2015), 29 September –1 October 2015, TH Hotel, Alor Setar, Kedah, Malaysia. http://doi.org/10.1063/1.4937070 doi:10.1063/1.4937070 doi:10.1063/1.4937070 |
| spellingShingle | QA75 Electronic computers. Computer science Mousa, Aseel Yusof, Yuhanis An improved Chebyshev distance metric for clustering medical images |
| title | An improved Chebyshev distance metric for clustering medical images |
| title_full | An improved Chebyshev distance metric for clustering medical images |
| title_fullStr | An improved Chebyshev distance metric for clustering medical images |
| title_full_unstemmed | An improved Chebyshev distance metric for clustering medical images |
| title_short | An improved Chebyshev distance metric for clustering medical images |
| title_sort | improved chebyshev distance metric for clustering medical images |
| topic | QA75 Electronic computers. Computer science |
| work_keys_str_mv | AT mousaaseel animprovedchebyshevdistancemetricforclusteringmedicalimages AT yusofyuhanis animprovedchebyshevdistancemetricforclusteringmedicalimages AT mousaaseel improvedchebyshevdistancemetricforclusteringmedicalimages AT yusofyuhanis improvedchebyshevdistancemetricforclusteringmedicalimages |