MULTI-CLASS REGION MERGING FOR INTERACTIVE IMAGE SEGMENTATION USING HIERARCHICAL CLUSTERING ANALYSIS

Main Authors: Aisyah, Khairiyyah Nur, Anggraini, Syadza, Putriwijaya, Novi Nur, Arifin, Agus Zainal, Indraswari, Rarasmaya, Navastara, Dini Adni
Format: Article info application/pdf eJournal
Bahasa: eng
Terbitan: Faculty of Computer Science - Universitas Indonesia , 2019
Subjects:
Online Access: http://jiki.cs.ui.ac.id/index.php/jiki/article/view/757
http://jiki.cs.ui.ac.id/index.php/jiki/article/view/757/418
Daftar Isi:
  • In interactive image segmentation, distance calculation between regions and sequence of region merging is being an important thing that needs to be considered to obtain accurate segmentation results. Region merging without regard to label in Hierarchical Clustering Analysis causes the possibility of two different labels merged into a cluster and resulting errors in segmentation. This study proposes a new multi-class region merging strategy for interactive image segmentation using the Hierarchical Clustering Analysis. Marking is given to regions that are considered as objects and background, which are then referred as classes. A different label for each class is given to prevent any classes with different label merged into a cluster. Based on experiment, the mean value of ME and RAE for the results of segmentation using the proposed method are 0.035 and 0.083, respectively. Experimental results show that giving the label on each class is effectively used in multi-class region merging.