Выдержка
In this paper the usage of multi-step segmentation for near-duplicate image recognition is investigated. The clustering of image pixels brightness is used for segmentation. The clustering is realized by means of a recurrent neural network. The search pattern based on the rank distributions of the brightness clusters cardinality is suggested. Experimental results on the near-duplicate image recognition based on the application of the suggested search pattern are given. It is shown that the use of a multi-step segmentation and rank distributions of the brightness clusters cardinality allows one to successfully recognize the duplicates, which are received by a considerable visual distortion of the original image or by the change of image scale.
| Язык оригинала | Английский |
|---|---|
| Страницы (с-по) | 811-817 |
| Число страниц | 7 |
| Журнал | Computer Optics |
| Том | 38 |
| Номер выпуска | 4 |
| Состояние | Опубликовано - 2014 |
Отпечаток
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering
- Computer Science Applications
Цитировать
Near-duplicate image recognition based on the rank distribution of the brightness clusters cardinality. / Nemirovskiy, V. B.; Stoyanov, A. K.
В: Computer Optics, Том 38, № 4, 2014, стр. 811-817.Результат исследований: Материалы для журнала › Статья
}
TY - JOUR
T1 - Near-duplicate image recognition based on the rank distribution of the brightness clusters cardinality
AU - Nemirovskiy, V. B.
AU - Stoyanov, A. K.
PY - 2014
Y1 - 2014
N2 - In this paper the usage of multi-step segmentation for near-duplicate image recognition is investigated. The clustering of image pixels brightness is used for segmentation. The clustering is realized by means of a recurrent neural network. The search pattern based on the rank distributions of the brightness clusters cardinality is suggested. Experimental results on the near-duplicate image recognition based on the application of the suggested search pattern are given. It is shown that the use of a multi-step segmentation and rank distributions of the brightness clusters cardinality allows one to successfully recognize the duplicates, which are received by a considerable visual distortion of the original image or by the change of image scale.
AB - In this paper the usage of multi-step segmentation for near-duplicate image recognition is investigated. The clustering of image pixels brightness is used for segmentation. The clustering is realized by means of a recurrent neural network. The search pattern based on the rank distributions of the brightness clusters cardinality is suggested. Experimental results on the near-duplicate image recognition based on the application of the suggested search pattern are given. It is shown that the use of a multi-step segmentation and rank distributions of the brightness clusters cardinality allows one to successfully recognize the duplicates, which are received by a considerable visual distortion of the original image or by the change of image scale.
KW - Clustering
KW - Image
KW - Image recognition
KW - Pixel
KW - Point mapping
KW - Ranking distribution
KW - Recurrent neural network
KW - Segmentation
UR - http://www.scopus.com/inward/record.url?scp=84922545284&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84922545284&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84922545284
VL - 38
SP - 811
EP - 817
JO - Computer Optics
JF - Computer Optics
SN - 0134-2452
IS - 4
ER -