Quantitative evaluation for simple segmentation SVM in landscape image

Endang Purnama Giri, Aniati Murni Arymurthy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Until now, designing a reliable image segmentation algorithm is still an open problem. Research related to this matter is still underway, but in one occasion we may be faced with the problem for selection image segmentation algorithms that will we use? To get the solution of this problem we need a good technical evaluation of image segmentation algorithms. With the technique, it is expected we can finally choose and use the right image segmentation algorithm. Pixel matching (Pm) an image segmentation algorithm evaluation techniques are common but considered less complete and does not support the refinement aspects evaluation. In this study we present two techniques for the evaluation of the segmentation algorithm: Local Consistency Error (LCE) and boundary matching. Furthermore both of techniques will use for evaluate segmentation algorithms based on Support Vector Machine (SVM) with a variety of simple features. In addition, as a comparison, k-mean will used as the base segmentation technique. From the experimental result showed that in general segmentation algorithm using SVM produces a better accuracy than k-means. The highest accuracy is obtained when the value is used as the SVM as classifier and Hue Saturate Value (HSV) as a feature. Sequentially evaluation value obtained was 90. 614% (Pm), 0.106 (LCE), and the highest value of precision and recall for matching boundary are 0.419 and 0.721 (when radius = 5 pixels).

Original languageEnglish
Title of host publicationProceedings - ICACSIS 2014
Subtitle of host publication2014 International Conference on Advanced Computer Science and Information Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages369-374
Number of pages6
ISBN (Electronic)9781479980758
DOIs
Publication statusPublished - 23 Mar 2014
Event2014 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2014 - Jakarta, Indonesia
Duration: 18 Oct 201419 Oct 2014

Publication series

NameProceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems

Conference

Conference2014 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2014
CountryIndonesia
CityJakarta
Period18/10/1419/10/14

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    Giri, E. P., & Arymurthy, A. M. (2014). Quantitative evaluation for simple segmentation SVM in landscape image. In Proceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems (pp. 369-374). [7065853] (Proceedings - ICACSIS 2014: 2014 International Conference on Advanced Computer Science and Information Systems). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACSIS.2014.7065853