Volume 32 #3

Contents

1. Fundamental principles of odor perception for higher fatty aids V. Ì. Ganshina and E. P. Zinkevich
2. Attractors for visual attention and visual scene analysis
3. Influence of the pre-exposure of visual objects on the discrimination of sounds in children with a delay in mental and language development
4. Neural network-based feature point descriptors for registration of optical and SAR images
5. Artificial training data generation for the task of character recognition of fields of russian passport
6. Methods of training data augmentation in the task of image classification
7. Neural network model of multisensory detector vehicle presence in the classification zone of charging points
8. Learning a metric feature space with siamese networks for disparity map computation
9. A method of object recognition based on formal properties specification applied to locating objects in aerial photographs

Registration of optical and SAR images is an important computer vision problem. Traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we propose new feature points description technique for the problem of registration of SAR and optical images. Feature points descriptors are build using siamese neural network. Experimental results are presented that confirm the method’s effectiveness.

Key words: optical and SAR image registration, feature points, siamese neural network, learning descriptors

DOI: 10.1134/S0235009218030034

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