Murinto, Murinto and Sri, Winiarti and Prahara, Adhi and Eko NW, febri (2018) Evolutionary Optimization Methods for Animal Leather Image Segmentation. [Artikel Dosen]
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Abstract
One of the processes undertaken to determine the quality of
animal skin for leather craft in the form of digital images is
the process of image segmentation. A disability detection
process is required to ensure that animal skins used for craft
are right-near as expected. In this research, the evolutionary
method is used to process Darwinian segmentation of particle
swarm optimization (DPSO) methods used for animal image
segmentation process. The results were then compared with
the Harmonic Search Algorithm (HSA) method. The process
of image segmentation is important, if segmentation is done
correctly then the next process will run correctly too. One of
the problems usually faced is how to choose a good image segmentation method. Experiments had been done on four categories of animal leather images namely lizard leather, sheep leather, cow leather and goat leather. PSNR values were used to measure the quality of the segmentation ethod used. From the experimental results it is seen that there is little difference between the DPSO and HSA methods used in this study. It can be ncluded, however, that the DPSO method is slightly better than the HSA in certain animal cases. PSNR value is higher when compared to using HSA methods on the same image.
| Item Type: | Artikel Dosen |
|---|---|
| Keyword: | Image segmentation, images leather, harmonic search algorithm, Darwinian particle swarm optimizations |
| Subjects: | Q Science > Q Science (General) |
| Divisi / Prodi: | Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Informatics Engineering (S1-Teknik Informatika) |
| Depositing User: | murinto murinto |
| Date Deposited: | 18 Apr 2023 09:48 |
| Last Modified: | 23 Sep 2023 05:54 |
| URI: | http://eprints.uad.ac.id/id/eprint/43014 |
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