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All Journal International Journal of Electrical and Computer Engineering
Puji Budi Setia Asih
Eijkman Institute for Molecular Biology
Computer Science & IT Electrical & Electronics Engineering

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Incorporating Index of Fuzziness and Adaptive Thresholding for Image Segmentation Umi Salamah; Riyanarto Sarno; Agus Zainal Arifin; Anto Satriyo Nugroho; Ismail Eko Prayitno Rozi; Puji Budi Setia Asih
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 4: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1192.007 KB) | DOI: 10.11591/ijece.v8i4.pp2406-2418

Abstract

Binary Segmentation of an image played 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 proposed 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 showed 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.
Co-Authors Agus Zainal Arifin Anto Satriyo Nugroho Ismail Eko Prayitno Rozi Riyanarto Sarno Umi Salamah