Abstract
The process of separating cell objects from a background is very important in cell image analysis and cell tracking. Most cell image histograms that have uneven illumination during microscopic cell imaging have a uni-modal distribution. In general, it is more difficult to segment objects in images having a uni-modal distribution than in those having a bi-modal or multi-modal distribution; therefore, images having a uni-modal distribution require a special segmentation algorithm that is more complicated and requires computing costs. If the histogram of the given cell image is known, an appropriate segmentation algorithm is applied for an accurate segmentation. In this paper, we proposed an algorithm that automatically determines the histogram distribution of an inputted cell image. The proposed method uses the polygonal approximation method. We tested this algorithm on various cell images and the error was found to be less than 5% on average.
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Abbreviations
- f(k):
-
the frequency of an intensity value k (0 ≤ k ≤ 255)
- Pk :
-
a pair of coordinates (k, f(k))
- H:
-
the point set that constitutes the histogram of a cell image
- Lij :
-
a straight li ne that passes the starting point Pi and the last position Pj
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Hong, D.P., Shim, J. & Cho, M. Determination of histogram type of cell images in microsystem for cell tracking. Int. J. Precis. Eng. Manuf. 15, 2673–2676 (2014). https://doi.org/10.1007/s12541-014-0641-1
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DOI: https://doi.org/10.1007/s12541-014-0641-1