Intelligent transportation systems are rapidly growing mainly due to active development of novel hardware and software solutions. In the paper a problem of automatical number plate detection is considered. An efficient two-step approach based on plate candidates extraction with further classification by neural network is proposed.
The number plate detection is a key step affecting the overall performance of the number plate recognition system. In the paper a novel algorithm for this purpose is proposed. The approach is based on the detection of text areas using the stroke width transform.
Formation of high-resolution SAR images from light-weight platforms is a challenging task primarily due to high instability of such platforms. Additional difficulties are related with the precision of navigation systems. In the paper the problem of residual trajectory deviations are analyzed. An efficient trajectory reconstruction method is proposed.
Multi-look processing is a well-known technique actively used in the SAR research community. In the paper, a method is described for the extraction of the ground moving targets parameters from a sequence of SAR look images obtained with a single-antenna SAR. The method calls for the automatic road extraction from the multi-look SAR images.
Autofocusing is one of the key steps in the high-resolution SAR imaging. In the paper several important improvements to the recently developed local-quadratic map-drift autofocus are proposed. Important SAR image preprocessing steps applied before the local Doppler rate errors estimation are described. The weighting scheme for the evaluation of residual cross-track acceleration components is developed.
The accuracy of trajectory measurements is one of the crucial factors in high-resolution SAR imaging. Common navigation systems often do not fulfill the requirements that results in significant image quality degradation. In the paper, a new autofocus algorithm for the reconstruction of the SAR platform trajectory deviations is proposed.
Synthetic aperture radar is a popular instrument for high-resolution imaging. Usage of state-of-the-art image and signal processing solutions allows to significantly increase the efficiency of such systems. In the paper two important applications of computer vision algorithms are described. In particular, usage of local feature extraction algorithms for the radar image stitching.
Two modifications of the range-Doppler algorithm (RDA) have been proposed to solve problems of SAR platform motion instabilities. First, the multi-look processing based on the RDA with an extended Doppler bandwidth has been introduced for correction of radiometric errors.
The quality of high-resolution SAR imaging is strictly related with the precision of the platform trajectory measurements. This is one of the crucial points in the case of image formation from light-weight aircrafts and UAV platforms, which undergone significant trajectory instabilities in real flight conditions.
In the paper, an X-band airborne SAR system developed and produced at the Institute of Radio Astronomy is described. The system is designed to be operated from light-weight aircrafts. Implemented hardware and real-time software solutions are discussed. Several original approaches to the post-processing of the recorded data are considered. Experimental results are also presented and discussed.