Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 811-817 |
| Number of pages | 7 |
| Journal | Computer Optics |
| Volume | 38 |
| Issue number | 4 |
| Publication status | Published - 2014 |
Keywords
- Clustering
- Image
- Image recognition
- Pixel
- Point mapping
- Ranking distribution
- Recurrent neural network
- Segmentation
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Electrical and Electronic Engineering
- Computer Science Applications