DETECTION OF TEXT OBJECTS IN IMAGES OF REAL SCENES BASED ON CONVOLUTIONAL NEURAL NETWORK MODEL
A model of text image detector based on a convolutional neural network architecture is presented, capable of synthesizing high-level features of images in the «black box» mode. An implementation of the detector application, based on algorithms of multi-scale scanning and local responses interpretati...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | Russian |
| Published: |
The United Institute of Informatics Problems of the National Academy of Sciences of Belarus
2016-09-01
|
| Series: | Informatika |
| Online Access: | https://inf.grid.by/jour/article/view/15 |
| Summary: | A model of text image detector based on a convolutional neural network architecture is presented, capable of synthesizing high-level features of images in the «black box» mode. An implementation of the detector application, based on algorithms of multi-scale scanning and local responses interpretation is described, allowing to find out text samples on images of real scenes. Advantages in comparison with analogs are shown and efficiency evaluation on an example of a known database is conducted. |
|---|---|
| ISSN: | 1816-0301 |