Similarity Measurement Of Segmented Image Using Euclidean Distance Method

DOI

10.2991/icm2e-18.2018.20How to use a DOI?

Keywords

Euclidean Distance Method, Image Segmentation, Similarity Measure.

Abstract

This research aim to measure the similarity of two image. The similarity measurement is used to get the original image of the segmented image. The query image is an image that suspected to get undergone a change. The query image must be segmented first before measuring process. The similarity measurement process use Euclidean distance method. The process undertaken to identify the image of the segmentation result is to segment the image of the database, determine the co-occurrence matrix of each image, perform the texture feature analysis of each image, then calculate the distance of the texture feature of each image. The image identification stage of the query image in the program begins by inputting the color image to be segmented, then the image of the database is segmented, followed by texture feature value analysis for image and image imagery in the database, and calculating the value of similarity texture feature using Euclidean Distance method.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Meira Parma Dewi
AU  - Silfinia
AU  - Dewi Murni
PY  - 2018/12
DA  - 2018/12
TI  - Similarity Measurement Of Segmented Image Using Euclidean Distance Method
BT  - Proceedings of the 2nd International Conference on Mathematics and Mathematics Education 2018 (ICM2E 2018)
PB  - Atlantis Press
SP  - 79
EP  - 84
SN  - 2352-5398
UR  - https://doi.org/10.2991/icm2e-18.2018.20
DO  - 10.2991/icm2e-18.2018.20
ID  - Dewi2018/12
ER  -