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http://dx.doi.org/10.9717/kmms.2017.20.6.845

LVQ_Merge Clustering Algorithm for Cell Image Extraction  

Kwon, Hee Yong (Dept of Computer Engineering, Anyang University)
Kim, Min Su (Dept of Computer Engineering, Anyang University)
Choi, Kyung Wan (Dept of Computer Engineering, Anyang University)
Kwack, Ho Jic (Dept of Computer Engineering, Anyang University)
Yu, Suk Hyun (Dept of Information & Communications Engineering, Anyang University)
Publication Information
Journal of Korea Multimedia Society / v.20, no.6, 2017 , pp. 845-852 More about this Journal
Abstract
In this paper, we propose a binarization algorithm using LVQ-Merge clustering method for fast and accurate extraction of cells from cell images. The proposed method clusters pixel data of a given image by using LVQ to remove noise and divides the result into two clusters by applying a hierarchical clustering algorithm to improve the accuracy of binarization. As a result, the execution speed is somewhat slower than that of the conventional LVQ or Otsu algorithm. However, the results of the binarization have very good quality and are almost identical to those judged by the human eye. Especially, the bigger and the more complex the image, the better the binarization quality. This suggests that the proposed method is a useful method for medical image processing field where high-resolution and huge medical images must be processed in real time. In addition, this method is possible to have many clusters instead of two cluster, so it can be used as a method to complement a hierarchical clustering algorithm.
Keywords
Clustering Algorithm; LVQ; Hierarchical Clustering; Cell Image; Binarization;
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Times Cited By KSCI : 1  (Citation Analysis)
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