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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/79668

    Title: A Novel Histogram-Based Multi-Threshold Searching Algorithm for Multilevel Color Thresholding
    Authors: Tsai, Chi-yi;Liu, Tsung-yen;Chen, Wei-chieh
    Contributors: 淡江大學電機工程學系
    Keywords: Multi-object;Segmentation;Multilevel Thresholding;Colour Thresholding;Multi-threshold Searching;Ratio-map Image
    Date: 2012-11-30
    Issue Date: 2013-01-08 13:59:51 (UTC+8)
    Publisher: Rijeka: InTech Open Access Publisher
    Abstract: Image segmentation is an important preliminary process required in object tracking applications. This paper addresses the issue of unsupervised multi‐colour thresholding design for colour‐based multiple objects segmentation. Most of the current unsupervised colour thresholding techniques require adopting a supervised training algorithm or a cluster‐number decision algorithm to obtain optimal threshold values of each colour channel for a colour‐of‐interest. In this paper, a novel unsupervised multi‐threshold searching algorithm is proposed to automatically search the optimal threshold values for segmenting multiple colour objects. To achieve this, a novel ratio‐map image computation method is proposed to efficiently enhance the contrast between colour and non¬colour pixels. The Otsu’s method is then applied to the ratio‐map image to extract all colour objects from the image. Finally, a new histogram‐based multi‐threshold searching algorithm is developed to search the optimal upper‐bound and lower‐bound threshold values of hue, saturation and brightness components for each colour object. Experimental results show that the proposed method not only succeeds in separating all colour objects-of-interest in colour images, but also provides satisfactory colour thresholding results compared with an existing multilevel thresholding method.
    Relation: International Journal of Advanced Robotic Systems 14(223:2012), pp.1-13
    DOI: 10.5772/52851
    Appears in Collections:[Graduate Institute & Department of Electrical Engineering] Journal Article

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