Detection of False Synchronization of Stereo Image Transmission Using a Convolutional Neural Network
| Autor: | Mariusz Kubanek, Joanna Kulawik |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Correctness Physics and Astronomy (miscellaneous) Computer science General Mathematics ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION stereo-vision convolutional neural network 02 engineering and technology Convolutional neural network 020901 industrial engineering & automation Stereo image Synchronization (computer science) 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) false synchronization of stereo streams Computer vision Degree of certainty business.industry lcsh:Mathematics lcsh:QA1-939 Base (topology) Stereopsis Transmission (telecommunications) Chemistry (miscellaneous) 020201 artificial intelligence & image processing Artificial intelligence business |
| Zdroj: | Symmetry, Vol 13, Iss 78, p 78 (2021) Symmetry Volume 13 Issue 1 |
| ISSN: | 2073-8994 |
| DOI: | 10.3390/sym13010078 |
| Popis: | The subject of the work described in this article is the detection of false synchronization in the transmission of digital stereo images. Until now, the synchronization problem was solved by using start triggers in the recording. Our proposal checks the discrepancy between the received pairs of images, which allows you to detect delays in transferring images between the left camera and the right camera. For this purpose, a deep network is used to classify the analyzed pairs of images into five classes: MuchFaster, Faster, Regular, Slower, and MuchSlower. As can be seen as a result of the conducted work, satisfactory research results were obtained as the correct classification. A high percentage of average probability in individual classes also indicates a high degree of certainty as to the correctness of the results. An author&rsquo s base of colorful stereo images in the number of 3070 pairs is used for the research. |
| Databáze: | OpenAIRE |
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