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http://dx.doi.org/10.9708/jksci.2013.18.8.027

Quantization of Lumbar Muscle using FCM Algorithm  

Kim, Kwang-Baek (Dept. of Computer Science, Silla University)
Publication Information
Journal of the Korea Society of Computer and Information / v.18, no.8, 2013 , pp. 27-31 More about this Journal
Abstract
In this paper, we propose a new quantization method using fuzzy C-means clustering(FCM) for lumbar ultrasound image recognition. Unlike usual histogram based quantization, our method first classifies regions into 10 clusters and sorts them by the central value of each cluster. Those clusters are represented with different colors. This method is efficient to handle lumbar ultrasound image since in this part of human body, the brightness values are distributed to doubly skewed histogram in general thus the usual histogram based quantization is not strong to extract different areas. Experiment conducted with 15 real lumbar images verified the efficacy of proposed method.
Keywords
Lumbar ultrasound image; Fuzzy C-means clustering; Quantization; Histogram;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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