eprintid: 3552
rev_number: 9
eprint_status: archive
userid: 285
dir: disk0/00/00/35/52
datestamp: 2019-08-21 03:35:43
lastmod: 2019-08-21 03:35:43
status_changed: 2019-08-21 03:35:43
type: article
metadata_visibility: show
creators_name: Dinh, Tran Hiep
creators_name: Phung, Manh Duong
creators_name: Ha, Quang
creators_id: tranhiep.dinh@vnu.edu.vn
creators_id: duongpm@vnu.edu.vn
creators_id: quang.ha@uts.edu.au
title: Summit Navigator: A Novel Approach for Local Maxima Extraction
ispublished: pub
subjects: ECE
subjects: ElectronicsandComputerEngineering
subjects: Scopus
subjects: isi
divisions: fac_fet
abstract: This paper presents a novel method, called the Summit Navigator, to effectively extract local maxima of an image histogram for multi-object segmentation of images. After smoothing with a moving average filter, the obtained histogram is analyzed, based on the data density and distribution to find the best observing location. An observability index for each initial peak is proposed to evaluate if it can be considered as dominant by using the calculated observing location. Recursive algorithms are then developed for peak searching and merging to remove any false detection of peaks that are located on one side of each mode. Experimental results demonstrated the advantages of the proposed approach in terms of accuracy and consistency in different reputable datasets.
date: 2019-08-15
date_type: published
publisher: IEEE
official_url: https://ieeexplore.ieee.org/document/8794719
id_number: 10.1109/TIP.2019.2932501
full_text_status: public
publication: IEEE Transactions on Image Processing
refereed: TRUE
issn: 1057-7149
citation:   Dinh, Tran Hiep and Phung, Manh Duong and Ha, Quang  (2019) Summit Navigator: A Novel Approach for Local Maxima Extraction.  IEEE Transactions on Image Processing .    ISSN 1057-7149     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3552/1/08794719.pdf