Karma, I Gede Made and Darma Putra, I Ketut Gede and Sudarma, Made and Linawati, Linawati (2022) Image Segmentation Based on Color Dissimilarity. Informatica, 46 (5). pp. 501-509. ISSN 0350-5596
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This study aims to develop a segmentation technique that can be used to detect objects in an image. The concept used is to imitate the human concept of recognizing an object based on its color difference. A color is considered different if it has different R, G or B values. Humans can only distinguish two colors clearly if they both have a DeltaE value of at least 8. The difference in DeltaE values is obtained from differences in the values of R, G or B, either alone or in pairs. The application of this concept to the segmentation technique has shown good results. This technique is able to give the same results and is good for images with JPG, PNG and BMP file types. To provide confidence in the performance of this method, a comparison is made with several segmentation methods. By measuring the similarity index using the Jaccard index, Sørensen–Dice index and BF Score, this color dissimilarity-based segmentation method has the best performance. Meanwhile, when measuring the processing time, this method has the second best performance. Thus, it can be concluded that this method is very suitable for detecting objects in an image. Povzetek: Tehnika segmentacije je bila razvita z imitacijo človeškega koncepta prepoznavanja predmeta, in sicer na podlagi barvnih razlik. Barve se štejejo za različne, če imajo vrednost DeltaE najmanj 8, ki jo dobimo iz razlik v vrednostih R, G ali B barv samih ali v parih. Izvajanje te tehnike kaže enake rezultate za datoteke JPG, PNG in BMP in je v veliko pomoč pri postopku identifikacije predmeta.
| Item Type: | Article |
|---|---|
| Subjects: | Ilmu Teknik > Teknik Elektro Dan Informatika > Teknik Informatika |
| Divisions: | Jurusan Akuntansi > Prodi D4 Akuntansi Manajerial > Publikasi |
| Depositing User: | I Gede Made Karma |
| Date Deposited: | 31 Aug 2022 04:59 |
| Last Modified: | 31 Aug 2022 04:59 |
| URI: | http://repository.pnb.ac.id/id/eprint/72 |
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