Method of image texture segmentation using Laws' energy measures
Fragment książki (Materiały konferencyjne)
MNiSW
15
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| Status: | |
| Autorzy: | Kvyetnyy Roman N., Sofina Olga, Olesenko Alla, Komada Paweł, Sikora Jan, Kalizhanova Aliya, Smailova Saule |
| Dyscypliny: | |
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| Wersja dokumentu: | Drukowana | Elektroniczna |
| Arkusze wydawnicze: | 0,5 |
| Język: | angielski |
| Strony: | 1784 - 1792 |
| Web of Science® Times Cited: | 0 |
| Scopus® Cytowania: | 15 |
| Bazy: | Web of Science | Scopus |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | TAK |
| Nazwa konferencji: | XL-th IEEE-SPIE Joint Symposium on Photonics, Web Engineering, Electronics for Astronomy and High Energy Physics Experiments |
| Skrócona nazwa konferencji: | XL SPIE-IEEE-PSP 2017 |
| URL serii konferencji: | LINK |
| Termin konferencji: | 28 maja 2017 do 6 czerwca 2017 |
| Miasto konferencji: | Wilga |
| Państwo konferencji: | POLSKA |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| This article suggests the method of image segmentation, using Laws' texture energy measures. This method allows identifying segments of images efficiently for their further use in the image processing. Laws` measures describe the image most accurately, resulting in making it easier and more efficient in comparison with the other approaches to allocate separate classes of textures. In order to obtain these measures the sixteen masks are calculated. Resulting energy measures can be provided after applying each of the masks to the image. The developed algorithm was tested using a set of test images. Analysis of the obtained results has showed that in case of visually similar texture images the transition to energy maps significantly improves the correlation coefficient and therefore emphasizes textural features of the images and makes it possible to identify the similarities of textures. In order to evaluate the results of efficiency of developed algorithm properly, its results have been compared to the segmentation method based on matrix matches. It was proved that segmentation based on Laws` measures can detect various types of texture more precisely and with greater speed of operation. |
