Artificial Intelligence Review

, Volume 51, Issue 4, pp 673–705 | Cite as

Niblack’s binarization method and its modifications to real-time applications: a review

  • Lalit Prakash SaxenaEmail author


Local binarization methods deal with the separation of foreground objects (textual content) and background noise (non-text) specifically at the pixel level. This is a much-explored field in the domain of documents image-processing that tends to separate the textual content from a degraded document. Since three decades, many local binarization methods have been developed to binarize documents images suffering from severe deteriorations. This paper presents a review of local binarization methods that are developed based on Niblack’s binarization method (NBM, developed in 1986) only. Further, this paper is a review of local binarization methods having more or less modifications to the original Niblack’s method, depending on the requirements of their model and the processed output. The modifications to NBM can be seen in various applications, such as deteriorated documents image binarization, manuscripts restoration, finding texts in video frames, revealing engraved wooden stamps, vehicle license plate number recognition, stained cytology nuclei detection and product barcodes reading. However, there could be a possibility of other applications using NBM with modifications based on the input images and the applications’ requirements.


Niblack’s method Binarization Mean Standard deviation Local thresholds Window size HDIBCO 2016 dataset Performance measures 


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© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Applied Research SectionCombo ConsultancyObraIndia

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