A neural network system model for active perception and invariant recognition of grey-level images
| Autor: | Valentina I. Gusakova, Lubov N. Podladchikova, Natalia A. Shevtsova, Alexander V. Golovan, Ilya A. Rybak |
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| Rok vydání: | 2003 |
| Předmět: |
Visual perception
Artificial neural network Active perception business.industry Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Image processing Invariant (physics) Spatial relation Computer Science::Computer Vision and Pattern Recognition Computer vision Artificial intelligence business |
| Zdroj: | [Proceedings 1992] IJCNN International Joint Conference on Neural Networks. |
| DOI: | 10.1109/ijcnn.1992.227348 |
| Popis: | A method for parallel-sequential processing of gray-level images and their representation which is invariant to position, rotation, and scale has been developed. The method is based on the idea that an image is memorized and recognized by way of consecutive fixations of moving eyes on the most informative image fragments. The method provides the invariant representation of the image in each fixation point and of spatial relations of features extracted in neighboring fixation points. A model of a neural network system for active visual perception and recognition of gray-level images has been developed based on this method. The experiments carried out with the model have shown that the system was able to recognize complex gray-level images in real time with invariance regarding position, rotation, and scale. > |
| Databáze: | OpenAIRE |
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