Abstract
Possibility of application of a recurrent neural network for segmentation of full-color images based on a clustering of color components is considered. Questions of multi-step segmentation of such images in different color models are discussed. Experimental results on multi-step segmentation of images are presented in the RGB and YUV color spaces.
| Original language | English |
|---|---|
| Title of host publication | 8th International Forum on Strategic Technology 2013, IFOST 2013 - Proceedings |
| Pages | 221-224 |
| Number of pages | 4 |
| Volume | 2 |
| DOIs | |
| Publication status | Published - 2013 |
| Event | 8th International Forum on Strategic Technology, IFOST 2013 - Ulaanbaatar, Mongolia Duration: 28 Jun 2013 → 1 Jul 2013 |
Conference
| Conference | 8th International Forum on Strategic Technology, IFOST 2013 |
|---|---|
| Country | Mongolia |
| City | Ulaanbaatar |
| Period | 28.6.13 → 1.7.13 |
Keywords
- clustering
- color space
- Image
- pixel
- point map
- recurrent neural network
- RGB
- segmentation
- YUV
ASJC Scopus subject areas
- Computer Networks and Communications
- Software
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Cite this
Nemirovskiy, V. B., & Stoyanov, A. K. (2013). Application of recurrent neural network for multi-step full-color image segmentation. In 8th International Forum on Strategic Technology 2013, IFOST 2013 - Proceedings (Vol. 2, pp. 221-224). [6616891] https://doi.org/10.1109/IFOST.2013.6616891