文章基本信息

标题：Incorporating Index of Fuzziness and Adaptive Thresholding for Image Segmentation
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作者：Umi Salamah ; Riyanarto Sarno ; Agus Zainal Arifin 等
期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2018
卷号：8
期号：4
页码：2406-2418
DOI：10.11591/ijece.v8i4.pp2406-2418
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：Binary Segmentation of an image play ed an important role in many image processing application. An image that was having no bimodal (or nearly) histogram accompanied by low-contrast was still a challenging segmentation problem to address. In this paper, we propose d a new segmentation strategy to images with very irregular histogram and had not significant contrast using index of fuzziness and adaptive thresholding. Index of fuzziness was used to determine the initial threshold, while adaptive thresholding was used to refine the coarse segmentation results. The used data were grayscale images from related papers previously. Moreover, the proposed method would be tested on the grayscale images of malaria parasite candidates from thickblood smear that had the same problem with this research. The experimental results show ed that the proposed method achieved higher segmentation accuracy and lower estimation error than other methods. The method also effective proven to segment malaria parasite candidates from thickblood smears image
其他摘要：Binary Segmentation of an image play ed an important role in many image processing application. An image that was having no bimodal (or nearly) histogram accompanied by low-contrast was still a challenging segmentation problem to address. In this paper, we propose d a new segmentation strategy to images with very irregular histogram and had not significant contrast using index of fuzziness and adaptive thresholding. Index of fuzziness was used to determine the initial threshold, while adaptive thresholding was used to refine the coarse segmentation results. The used data were grayscale images from related papers previously. Moreover, the proposed method would be tested on the grayscale images of malaria parasite candidates from thickblood smear that had the same problem with this research. The experimental results show ed that the proposed method achieved higher segmentation accuracy and lower estimation error than other methods. The method also effective proven to segment malaria parasite candidates from thickblood smears image
关键词：Index of Fuzziness Adaptive Thresholding Bimodal Significant contrast Very irregular histogram