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In image processing, the balanced histogram thresholding method (BHT),〔A. Anjos and H. Shahbazkia. Bi-Level Image Thresholding - A Fast Method. BIOSIGNALS 2008. Vol:2. P:70-76.〕 is a very simple method used for automatic image thresholding. Like Otsu's Method〔Nobuyuki Otsu (1979). "A threshold selection method from gray-level histograms". IEEE Trans. Sys., Man., Cyber. 9: 62–66.〕 and the Iterative Selection Thesholding Method,〔Ridler TW, Calvard S. (1978) Picture thresholding using an iterative selection method, IEEE Trans. System, Man and Cybernetics, SMC-8: 630-632.〕 this is a histogram based thresholding method. This approach assumes that the image is divided in two main classes: The background and the foreground. The BHT method tries to find the optimum threshold level that divides the histogram in two classes. This method ''weighs'' the histogram, checks which of the two sides is heavier, and removes weight from the heavier side until it becomes the lighter. It repeats the same operation until the edges of the weighing scale meet. Given its simplicity, this method is a good choice as a first approach when presenting the subject of ''automatic image thresholding''. ==Algorithm== The following listing, in C notation, is a simplified version of the Balanced Histogram Thresholding method:
This method may have problems when dealing with very noisy images, because the ''weighing scale'' may be misplaced. The problem can be minimized by ignoring the extremities of the histogram.〔A. Anjos, R. Leite, M. L. Cancela, H. Shahbazkia. MAQ – A Bioinformatics Tool for Automatic Macroarray Analysis. International Journal of Computer Applications. 2010. Number 7 - Article 1.〕 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Balanced histogram thresholding」の詳細全文を読む スポンサード リンク
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