KOMBINASI METODE GAUSSIAN FILTER DAN GAMMA CORRECTION UNTUK PERBAIKAN CITRA PADA SEGMENTASI SEL NUKLEUS CITRA PAP SMEAR

ANNAS, MUHAMMAD AZWAR and Dewi, Novi Rustiana and Irmeilyana, Irmeilyana (2022) KOMBINASI METODE GAUSSIAN FILTER DAN GAMMA CORRECTION UNTUK PERBAIKAN CITRA PADA SEGMENTASI SEL NUKLEUS CITRA PAP SMEAR. Undergraduate thesis, Sriwijaya University.

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Abstract

The nucleus is an important element in cervical cells that will undergo significant changes if someone is exposed to cervical cancer. Early detection of cervical cancer can be done using pap smear image segmentation by separating the nuclear and cytoplasmic cells. However, the pap smear image from the Zenodo dataset is still not good, so an image improvement process is needed. The image improvement process carried out in this study is using the Gaussian filter and the gamma correction methods. The segmentation process is continued by using the Otsu thresholding method. This research used data from the Zenodo dataset as input for the Pap smear image and then this data is converted into a grayscale image and then continued with the image improvement process using the Gaussian filter and gamma correction methods. Furthermore, the segmentation process is carried out using the Otsu thresholding method. The performance output of image improvement with MSE (Mean Square Error) is 3.260395, 43.11875 dB for PSNR (Peak Signal to Noise Ratio) and 0.9980594 for SSIM (Structural Similarity Index Metrics). The performance of image segmentation results in the form of an accuracy of 96.31%, sensitivity of 96.84% and specificity of 94.55%. Based on the MSE, PSNR and SSIM values, the results of the image repair that have been carried out are good and the performance of the segmentation results obtained is quite accurate.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Perbaikan Citra, Pap Smear, Gaussian Filter, Gamma Correction, Otsu Thresholding
Subjects:	Q Science > QA Mathematics > QA8.9-QA10.3 Computer science. Artificial intelligence. Computational complexity. Data structures (Computer scienc. Mathematical Logic and Formal Languages
Divisions:	08-Faculty of Mathematics and Natural Science > 44201-Mathematics (S1)
Depositing User:	S. Si Muhammad Azwar Annas
Date Deposited:	19 Dec 2023 01:22
Last Modified:	19 Dec 2023 01:22
URI:	http://repository.unsri.ac.id/id/eprint/134788

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