Lubov Podladchikova

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Colour and shape are basic characteristics of traffic signs which are used both by the driver and to develop artificial traffic sign recognition systems. However, these sign features have not been represented robustly in the earlier developed recognition systems, especially in disturbed viewing conditions. In this study, this information is represented by(More)
A biologically plausible model of traffic sign detection and recognition invariantly with respect to variable viewing conditions is presented. The model simulates several key mechanisms of biological vision, such as space-variant representation of information (reduction in resolution from the fovea to retinal periphery), orientation selectivity in the(More)
During the last 10 years, computer hardware technology has been improved rapidly. Large memory, storage is no longer a problem. Therefore some trade-off (dirty and quick algorithms) for traffic sign recognition between accuracy and speed should be improved. In this study, a new approach has been developed for accurate and fast recognition of traffic signs(More)
A model ol c an iso-orientation domain in the visual cortex is developed. The iso-orientation domain is represented as a neural network with retinotopieally organized t{fferent inputs and anisotropic lateral inhibition formed by feedbacks via inhibitor), interneurons'. Temporal dynamics of neuron responses to oriented stimuli is studied. The results off(More)
Earlier 13,18,19 , the biologically plausible active vision ,model for Multiresolutional Attentional Representation and Recognition (MARR) has been developed. The model is based on the scanpath theory of Noton and Stark 17 and provides invariant recognition of gray-level images. In the present paper, the algorithm of automatic image viewing trajectory(More)
Algorithms and procedures to solve the task of road sign detection and recognition invariant of viewing conditions and results of testing during computer simulation with British and Russian signs are presented. After preliminary colour segmentation of initial real world images and classification according to road sign colours and external forms,(More)
A new approach for the detection of head motions during PET scanning is presented. The proposed system includes 4 modules, which are: input module, face segmentation, facial landmark detection, and head movement estimation. The developed system is tested on pictures monitoring a subject's head while simulating PET scanning (n=12) and face images of subjects(More)
At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation(More)