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• W2999438316 abstract "Histogram-based thresholding is one of the widely applied techniques for conducting color image segmentation. The key to such techniques is the selection of a set of thresholds that can discriminate objects and background pixels. Many thresholding techniques have been proposed that use the shape information of histograms and identify the optimum thresholds at valleys. In this work, we introduce the novel concept of a hierarchical-histogram, which corresponds to a multigranularity abstraction of the color image. Based on this, we present a new histogram thresholding-Adaptive Hierarchical-Histogram Thresholding (AHHT) algorithm, which can adaptively identify the thresholds from valleys. The experimental results have demonstrated that the AHHT algorithm can obtain better segmentation results compared with the histon-based and the roughness-index-based techniques with drastically reduced time complexity." @default.
• W2999438316 created "2020-01-23" @default.
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• W2999438316 date "2020-01-10" @default.
• W2999438316 modified "2023-09-26" @default.
• W2999438316 title "Color image segmentation using adaptive hierarchical-histogram thresholding" @default.
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• W2999438316 doi "https://doi.org/10.1371/journal.pone.0226345" @default.
• W2999438316 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6953780" @default.
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