Survey over image thresholding techniques and quantitative performance evaluation

Survey over image thresholding techniques and quantitative performance evaluation. Sezgin, M. & Sankur, B. Journal of Electronic Imaging, 13(1):146-168, 2004.

Paper doi abstract bibtex

We conduct an exhaustive survey of image thresholding methods, categorize them, express their formulas under a uniform notation, and finally carry their performance comparison. The thresholding methods are categorized according to the information they are exploiting, such as histogram shape, measurement space clustering, entropy, object attributes, spatial correlation, and local gray-level surface. 40 selected thresholding methods from various categories are compared in the context of nondestructive testing applications as well as for document images. The comparison is based on the combined performance measures. We identify the thresholding algorithms that perform uniformly better over nondestructive testing and document image applications. � 2004 SPIE and IS&T.

@Article{sezgin04survey,
  author    = {Sezgin, Mehmet and Sankur, Bu�lent},
  journal   = {Journal of Electronic Imaging},
  title     = {Survey over image thresholding techniques and quantitative performance evaluation},
  year      = {2004},
  number    = {1},
  pages     = {146-168},
  volume    = {13},
  abstract  = {We conduct an exhaustive survey of image thresholding methods, categorize them, express their formulas under a uniform notation, and finally carry their performance comparison. The thresholding methods are categorized according to the information they are exploiting, such as histogram shape, measurement space clustering, entropy, object attributes, spatial correlation, and local gray-level surface. 40 selected thresholding methods from various categories are compared in the context of nondestructive testing applications as well as for document images. The comparison is based on the combined performance measures. We identify the thresholding algorithms that perform uniformly better over nondestructive testing and document image applications. � 2004 SPIE and IS&amp;T.},
  doi       = {10.1117/1.1631315},
  isbn      = {1017-9909},
  owner     = {Purva},
  timestamp = {2017-08-02},
  url       = {http://dx.doi.org/10.1117/1.1631315},
}

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