SEGMENTASI CITRA WARNA MENGGUNAKAN K-MEANS CLUSTERING

AYUDYAWATI, RACHMA and Samsuryadi, Samsuryadi and Rodiah, Desty (2019) SEGMENTASI CITRA WARNA MENGGUNAKAN K-MEANS CLUSTERING. Undergraduate thesis, Sriwijaya University.

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Abstract

This research used HSV, CIELAB and YCbCr color space that transformed from RGB images and color image segmentation with K-Means clustering. Each color space is determined by its chromaticity value, this chromaticity value becomes the input parameter in K-Means. The best segmentation quality is used using Probabilistic Rand Index (PRI), the higher the PRI value, the higher the level of similarity the result of segmentation. The result of segmentation of animal objects that have the highest similarity in the CIELab color space and HSV and YCbCr color space have the same amount of similarity.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Segmentasi citra warna,ruang warna, nilai formatisitas, k-mean klastering, probability land indeks
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Users 3297 not found.
Date Deposited:	25 Nov 2019 04:42
Last Modified:	25 Nov 2019 04:42
URI:	http://repository.unsri.ac.id/id/eprint/18094

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