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Hyun Jun Park
Pusan National University
Computer Science & IT Electrical & Electronics Engineering

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Automatic Segmentation of Brachial Artery based on Fuzzy C-Means Pixel Clustering from Ultrasound Images Joonsung Park; Doo Heon Song; Hosung Nho; Hyun-Min Choi; Kyung-Ae Kim; Hyun Jun Park; Kwang Baek Kim
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 2: April 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (514.778 KB) | DOI: 10.11591/ijece.v8i2.pp638-643

Abstract

Automatic extraction of brachial artery and measuring associated indices such as flow-mediated dilatation and Intima-media thickness are important for early detection of cardiovascular disease and other vascular endothelial malfunctions. In this paper, we propose the basic but important component of such decision-assisting medical software development – noise tolerant fully automatic segmentation of brachial artery from ultrasound images. Pixel clustering with Fuzzy C-Means algorithm in the quantization process is the key component of that segmentation with various image processing algorithms involved. This algorithm could be an alternative choice of segmentation process that can replace speckle noise-suffering edge detection procedures in this application domain.
Vision-based Crack Identification on the Concrete Slab Surface using Fuzzy Reasoning Rules and Self-Organizing Kwang Baek Kim; Hyun Jun Park; Doo Heon Song
International Journal of Electrical and Computer Engineering (IJECE) Vol 6, No 4: August 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (892.538 KB) | DOI: 10.11591/ijece.v6i4.pp1577-1586

Abstract

Identifying cracks on the surface of concrete slab structure is important for structure stability maintenance. In order to avoid subjective visual inspection, it is necessary to develop an automated identification and measuring system by vision based method. Although there have been some intelligent computerized inspection methods, they are sensitive to noise due to the brightness contrast and objects such as forms and joints of certain size often falsely classified as cracks. In this paper, we propose a new fuzzy logic based image processing method that extracts cracks from concrete slab structure including small cracks that were often neglected as noise. We extract candidate crack areas by applying fuzzy method with three color channel values of concrete slab structure. Then further refinement processes are performed with Self Organizing Map algorithm and density based noise removal process to obtain basic crack characteristic attributes for further analysis. Experimental result verifies that the proposed method is sufficiently identified cracks with various sizes with high accuracy (97.3%) among 1319 ground truth cracks from 30 images.
Co-Authors Doo Heon Song Hosung Nho Hyun-Min Choi Joonsung Park Kwang Baek Kim Kyung-Ae Kim