Turhan Tunali

Automatic number plate information extraction and recognition for intelligent transportation system

Abstract In this paper, a new license plate information retrieval system is designed and developed. The system has two main modules: segmentation and recognition. In segmentation, interested information on the image is extracted through the processes of Kaiser resizing, morphological filtering, artificial shifting and bi-directional vertical thresholding. In recognition module, a novel approach for principal component analysis (PCA) and fast backpropagation neural net composition is used as a recognizer. The novel approach is about the construction of Eigen space through the PCA that is used for feature extraction. Our approach is more tolerable to the problems of classical application PCA such as rotation, scaling and character width dependence. The outputs of the new feature extractor used as inputs to the fastbackpropagation neural net recognizer module. This neural network trained with scaled conjugate gradient function. For each module, alternative available methods are mentioned and proper sequence of operations is developed. Finally, overall performance of the system is exported.

Adaptive available bandwidth estimation for internet video streaming

In this study, an adaptive available bandwidth estimation approach that is suitable for Internet video streaming is developed. The algorithm exploits repetitive measurements and uses this redundancy to improve its video adaptation decision. The importance of available bandwidth estimation in Internet applications has recently increased particularly because of the heterogeneity of the network links. Many of the Internet paths may contain wired and wireless links in which loss may happen due to congestion as well as link errors. Hence, loss rate by itself is not a sufficient statistics for monitoring purposes. If the loss is due to congestion, video quality can then be decreased whereas if the loss is due to link error, no such action is necessary. Moreover, in video streaming, such an estimate can be used to determine the new video rate if the quality is to be increased. In our approach, active probing packets are used to estimate bandwidth in very short time duration. The novelty of our estimator is its adaptivity in the sense that the overhead caused by the estimator is automatically reduced when congestion builds up. The trade off is reduced accuracy. Such accuracy is not needed under congestion anyway and when things get back to normal, our estimator turns back to normal operation mode. We have integrated our algorithm into our video streamer and carried out experiments on both simulated and actual streaming applications on the Internet. The results indicate that our estimator algorithm increases streaming performance substantially.

Adaptive Streaming of Scalable Stereoscopic Video Over DCCP

We propose a new adaptive streaming model that utilizes DCCP in order to efficiently stream stereoscopic video over the Internet for 3DTV transport. The model allocates the available channel bandwidth, which is calculated by the DCCP, among the views according to the suppression theory of human vision. The video rate is adapted to the DCCP rate for each group of pictures (GoP) by adaptive extraction of layers from a scalable multi-view bitstream. The objective of the streaming model is to maximize perceived quality of the received 3D video while minimizing the number of possible display interrupts. Experimental results successfully demonstrate stereo video streaming over DCCP on wide area network.

Rate adaptive video streaming under lossy network conditions

In this study, the performance of a rate adaptive video streaming algorithm is examined under controlled packet loss rates and delays. The developed algorithm is a set of heuristics that consider the packet loss rate and receiver buffer level during the adaptation decision. The algorithm is content aware in such a way that it employs quality or temporal scaling, or both, in accordance with the amount of motion in a scene. Extensive periodic and non-periodic packet loss scenarios are implemented to examine the behavior of the algorithm. It has been observed that the algorithm reacts to congestion by reducing its data rate and maintain interrupt-free display even if the continuous packet loss rate approaches 15%. The results of this study confirm the suitability of our algorithm for Internet video streaming where congestion can occur any time unpredictably.

Design and Implementation of a Streaming System for MPEG-1 Videos

A new streaming application has been developed for the Internet environment. The system has client-server structure together with multithreaded architecture and pipelining. RTP protocol is used to transmit packets belonging to MPEG videos. RTCP protocol collects transmission statistics. System is adaptive in the sense that it reacts to dynamic network conditions. A feedback mechanism controls both the frame interval and frame rate depending on the frame-loss statistics and buffered video level at the client. A flow control module at the client side controls buffer underflows and overflows. Performance results of the implementation are reported and discussed. The performance of the proposed buffering strategy is compared with other proposed methods from the literature. The comparisons showed that the proposed strategy is more robust than other methods.

License plate segmentation for intelligent transportation systems

A license plate segmentation system is designed and developed. The system has preprocessing, approximate region finding, plate extraction and character segmentation modules. For each module, alternative available methods are examined and proper sequence of operations is developed. In character segmentation module, a novel method is devised. Finally, overall performance of the system is reported.

A Video Streaming Application on the Internet

A new software only streaming application is being developed for the Internet. The application is based on multithreaded architecture. RTP (Real-time Transport Protocol) is being used for the transmission of video data. The system is adaptive to dynamic network conditions. In this paper, performance results of the implementation are reported.

The design and implementation of a streaming application for MPEG videos

A new software-only video on demand system is being developed for the Internet environment. The system is based on multithreaded architecture. The RTP protocol is used to transmit packets belonging to MPEG videos. The RTCP protocol collects transmission statistics. The system is adaptive in the sense that it reacts to dynamic network conditions. Bandwidth allocation is performed according to the sizes of MPEG videos.

Bandwidth-Aware Scaling for Internet Video Streaming

In this study, we propose a bandwidth-aware scaling mechanism for rate adaptive video streaming. This mechanism involves estimation of the capacity of the network dynamically by measuring bottleneck bandwidth and available bandwidth values. By taking the available bandwidth as an upper limit, the sender adjusts its output rate accordingly. While increasing the quality of the video, using a bandwidth estimator instead of probing prevents the congestion generated by the streaming application itself. The results of the bandwidth-aware algorithm are compared with that of a similar algorithm with no bandwidth-aware scaling and the improvement is demonstrated with measurements taken over WAN.

SymPaD: Symbolic Patch Descriptor

We propose a new local image descriptor named SymPaD for image understanding. SymPaD is a probability vector associated with a given image pixel and represents the attachment of the pixel to a previously designed shape repertoire. As such the approach is model-driven. The SymPad descriptor is illumination and rotation invariant, and extremely flexible on extending the repertoire with any parametrically generated geometrical shapes and any desired additional transformation types.