Summit Navigator: A Novel Approach for Local Maxima Extraction

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...

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Bibliographic Details
Published inIEEE transactions on image processing Vol. 29; pp. 551 - 564
Main Authors Dinh, Tran Hiep, Phung, Manh Duong, Ha, Quang Phuc
Format Journal Article
LanguageEnglish
Published United States IEEE 01.01.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
histogram analysis
histogram segmentation
Histograms
Image segmentation
Indexes
Merging
Multi-thresholding
Navigation
Observability
summit navigator
Thresholding (Imaging)
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Summary: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.
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ISSN:1057-7149
1941-0042
1941-0042
DOI:10.1109/TIP.2019.2932501