Dena Mohamed Abdelsadek
Demonstrator
Impact of Using Different Color Spaces on the Image Segmentation
Advances in Machine Learning and Trends in Applications (AMLTA 2022) • 2022
Publication Information
Authors
Dena A. Abdelsadek; Maryam N. Al-Berry; Hala M. Ebied; Mosab Hassaan
Keywords
Image Segmentation; Color Spaces; RGB; YCbCr; XYZ; HSV; K-means; Fuzzy C-means; Region Growing; Graph Cut; Image Processing
Journal
Advances in Machine Learning and Trends in Applications (AMLTA 2022)
Publisher
Springer Nature Switzerland AG
Volume
113
Issue
Not Available
Pages
456-471
publication.type
International
Paper Link
Open Link
Supplementary Materials
Not Available
Abstract
This paper compares the performance of RGB, YCbCr, XYZ, and HSV color spaces in image segmentation. Four segmentation techniques, namely K-means, Fuzzy C-means, Region Growing, and Graph Cut, are evaluated using color images from the Berkeley database. The results indicate that combining color components can improve segmentation accuracy.