A novel approach for the hardware implementation of a PPMC statistical data compressor

This thesis aims to understand how to design high-performance compression algorithms suitable for hardware implementation and to provide hardware support for an efficient compression algorithm. Lossless data compression techniques have been developed to exploit the available bandwidth of applications in data communications and computer systems by reducing the amount of data they transmit or store. As the amount of data to handle is ever increasing, traditional methods for compressing data become· insufficient. To overcome this problem, more powerful methods have been developed. Among those are the so-called statistical data compression methods that compress data based on their statistics. However, their high complexity and space requirements have prevented their hardware implementation and the full exploitation of their potential benefits. This thesis looks into the feasibility of the hardware implementation of one of these statistical data compression methods by exploring the potential for reorganising and restructuring the method for hardware implementation and investigating ways of achieving efficient and effective designs to achieve an efficient and cost-effective algorithm. [Continues.

Towards a reconfigurable hardware architecture for implementing a LDPC module suitable for software radio systems

Forward Error Correction is a key piece in modern digital communications. When a signal is transmitted over a noisy channel, multiple errors are generated. FEC techniques are directed towards the recovery of such errors. In last years, LDPC (Low Density Parity Check) codes have attracted attention of researchers because of their excellent error correction capabilities, but for actual radios high performance is not enough since they require to communicate with other multiple radios too. In general, communication between multiple radios requires the use of different standards. In this sense, Software Defined Radio (SDR) approach allows building multi standard radios based on reconfigurability abilities which means that base components including recovery errors block must provide reconfigurable options. In this paper, some open problems in designing and implementing reconfigurable LDPC components are presented and discussed. Some features of works in the state of the art are commented and possible research lines proposed

Collision Detection in Cluttered Driving Scenes

The purpose of the present experiment was to examine whether drivers’ detection of collisions was altered when the driving scene was cluttered with scene objects. In this experiment stationary scene objects were manipulated by positioning them behind an approaching object and driver motion induced. We found that observers’ collision detection performance (d’) decreased with the presence of scene objects. These results indicate that the ability to detect a collision is altered by the presence of scene objects. In addition, performance was dependent on display duration, with greater sensitivity at increased durations. Moreover, the results showed a significant criterion shift between scene objects present and scene objects absent, with a decrease in identifying a collision object (hit rate) when scene objects were present but no difference in identification of a collision event when scene objects were absent. This suggests that the decreased performance was due to the inability to accurately determine a collision event because of apparent motion of background scene objects due to driver motion. Because the displays used in this experiment are akin to driving in a cluttered environment, the results of this research have important implications regarding driving safety and crash rates particularly in urban environments with complex scenes. Specifically, the results suggest that one factor in cluttered driving scenes is the apparent motion of background scene objects due to driver motion

Towards a Video Passive Content Fingerprinting Method for Partial-Copy Detection Robust against Non-Simulated Attacks.

Passive content fingerprinting is widely used for video content identification and monitoring. However, many challenges remain unsolved especially for partial-copies detection. The main challenge is to find the right balance between the computational cost of fingerprint extraction and fingerprint dimension, without compromising detection performance against various attacks (robustness). Fast video detection performance is desirable in several modern applications, for instance, in those where video detection involves the use of large video databases or in applications requiring real-time video detection of partial copies, a process whose difficulty increases when videos suffer severe transformations. In this context, conventional fingerprinting methods are not fully suitable to cope with the attacks and transformations mentioned before, either because the robustness of these methods is not enough or because their execution time is very high, where the time bottleneck is commonly found in the fingerprint extraction and matching operations. Motivated by these issues, in this work we propose a content fingerprinting method based on the extraction of a set of independent binary global and local fingerprints. Although these features are robust against common video transformations, their combination is more discriminant against severe video transformations such as signal processing attacks, geometric transformations and temporal and spatial desynchronization. Additionally, we use an efficient multilevel filtering system accelerating the processes of fingerprint extraction and matching. This multilevel filtering system helps to rapidly identify potential similar video copies upon which the fingerprint process is carried out only, thus saving computational time. We tested with datasets of real copied videos, and the results show how our method outperforms state-of-the-art methods regarding detection scores. Furthermore, the granularity of our method makes it suitable for partial-copy detection; that is, by processing only short segments of 1 second length