FPGA applications in signal and image processing

The increasing demand for real-time and smart digital signal processing (DSP) systems, calls for a better platform for their implementation. Most of these systems (e.g. digital image processing) are highly parallelisable, memory and processor hungry; such that the increasing performance of today�s general-purpose microprocessors are no longer able to handle them. A highly parallel hardware architecture, which offers enough memory resources, offers an alternative for such DSP implementations

A single-chip FPGA implementation of real-time adaptive background model

This paper demonstrates the use of a single-chip FPGA for the extraction of highly accurate background models in real-time. The models are based on 24-bit RGB values and 8-bit grayscale intensity values. Three background models are presented, all using a camcorder, single FPGA chip, four blocks of RAM and a display unit. The architectures have been implemented and tested using a Panasonic NVDS60B digital video camera connected to a Celoxica RC300 Prototyping Platform with a Xilinx Virtex II XC2v6000 FPGA and 4 banks of onboard RAM. The novel FPGA architecture presented has the advantages of minimizing latency and the movement of large datasets, by conducting time critical processes on BlockRAM. The systems operate at clock rates ranging from 57MHz to 65MHz and are capable of performing pre-processing functions like temporal low-pass filtering on standard frame size of 640X480 pixels at up to 210 frames per second

Digital signal processing: the impact of convergence on education, society and design flow

Design and development of real-time, memory and processor hungry digital signal processing systems has for decades been accomplished on general-purpose microprocessors. Increasing needs for high-performance DSP systems made these microprocessors unattractive for such implementations. Various attempts to improve the performance of these systems resulted in the use of dedicated digital signal processing devices like DSP processors and the former heavyweight champion of electronics design – Application Specific Integrated Circuits. The advent of RAM-based Field Programmable Gate Arrays has changed the DSP design flow. Software algorithmic designers can now take their DSP algorithms right from inception to hardware implementation, thanks to the increasing availability of software/hardware design flow or hardware/software co-design. This has led to a demand in the industry for graduates with good skills in both Electrical Engineering and Computer Science. This paper evaluates the impact of technology on DSP-based designs, hardware design languages, and how graduate/undergraduate courses have changed to suit this transition

A spatially distributed model for foreground segmentation

Foreground segmentation is a fundamental first processing stage for vision systems which monitor real-world activity. In this paper we consider the problem of achieving robust segmentation in scenes where the appearance of the background varies unpredictably over time. Variations may be caused by processes such as moving water, or foliage moved by wind, and typically degrade the performance of standard per-pixel background models. Our proposed approach addresses this problem by modeling homogeneous regions of scene pixels as an adaptive mixture of Gaussians in color and space. Model components are used to represent both the scene background and moving foreground objects. Newly observed pixel values are probabilistically classified, such that the spatial variance of the model components supports correct classification even when the background appearance is significantly distorted. We evaluate our method over several challenging video sequences, and compare our results with both per-pixel and Markov Random Field based models. Our results show the effectiveness of our approach in reducing incorrect classifications

Exploring the challenges encountered in managing diversity and inclusion in the telecommunications industry by selected multinationals in Ghana.

Doctoral Degree. University of KwaZulu-Natal, Durban.This study investigated the challenges encountered as well as examined the elements influencing the management of diversity and inclusion by multinationals in the telecommunications industry in Ghana. Diversity and inclusion are emerging aspects of management, which hinge on disciplines such as sociology and psychology and have been established by scholars to be a potent management tool in the globalised world. Africa and for that matter, Ghana, a West African state, has not been featured adequately in the emerging literature of diversity and inclusion. A sensitive aspect of the Ghanaian economy is the telecommunications sector. However, little is known about the challenges encountered by multinationals in the telecommunications industry regarding the management of diversity and inclusion in Ghana. Secondly, the elements influencing diversity and inclusion management is relatively unknown. Thus, the study was necessitated by the country's diversity, a vibrant economy in the last decades with telecommunications as one of its main drivers and enhanced democratic credentials. Further, the situation attracts individuals and organisations from other nations deepening the already diverse nature of the country. A qualitative (case study approach) approach was employed to answer the research questions and realise the objectives. In line with the tenets of the chosen methodology, which requires data absoluteness, the interviewees and focus group members were purposively selected through expert and maximum variation sampling respectively. There were three in-depth interviews and two focus group discussions conducted in the selected organisations, being the two market leaders in the telecommunication industry (MTN-Ghana and Vodafone–Ghana) in Ghana. Coding and thematic analysis were employed to identify the challenges and elements influencing the management of diversity and inclusion in the selected organisations. Challenges in managing diversity and inclusion regarding demographics, socio-cognitive and organisational diversities were identified. In addition, challenges associated with the economic condition, historical context, government, corporate and organisational policies as well as elements (ethnicity, corporate and government policies) influencing the management of diversity and inclusion in the organisations under study were identified, contributing to theory in this regard. In practice, the findings point to the fact that corporate policies or strategies are not adequately aligned to the societal context. The study further shows that an individual's social construct influences his or her sense of belonging. A proposed framework was created out of the findings of the study, aiming at mitigating the identified challenges, leading to a deeper understanding of the phenomenon. Arising from the findings of the study, it was recommended that further studies are needed to make the socio-cultural dynamics more explicit and align it to corporate strategies. In addition, the study needs to be broadened by employing mixed-method and include the entire number of organisations in the industry to obtain a conclusive result. More importantly, further studies are needed to highlight the impact of diversity and inclusion management on the bottom-line of organisations. The appreciation of the impact of diversity and inclusion on organisations will increase its significance as a management tool

Continuity and Discontinuity in Traditional African Narrative Ethics

There is much agreement today about the varied and important human functions of the act of narrating, and there is a long history of research behind storytelling. This paper joins the discussion from the perspective of the relation between ethics and narrative in the context of West African storytelling. The paper sketches the theory of narrative ethics generally and then focuses on West African narrative ethics. The main thesis concerns the existence of two parallel narratives of and about West Africa or the whole of Africa for that matter. There is what the paper calls the “traditional” narrative, which as a result of historical experiences of domination and colonialism has been progressively replaced by a “conventional” narrative. The paper argues that becoming the story about and by Africans, the conventional narrative engendered a loss of cultural memory among many African peoples. This is seen as a discontinuity of the “traditional” African (self-reflexive) narrative. Given the major role of narrative in Africa and the significance of narrative for ethics, the paper suggests that understanding the nature of the discontinuity of West African narrative can provide a paradigm for explaining some ethical challenges in the sub-region. Keywords: narrative ethics, identity, West African narrative, othernes

An FPGA-based infant monitoring system

We have designed an automated visual surveillance system for monitoring sleeping infants. The low-level image processing is implemented on an embedded Xilinx’s Virtex II XC2v6000 FPGA and quantifies the level of scene activity using a specially designed background subtraction algorithm. We present our algorithm and show how we have optimised it for this platform

Binary object recognition system on FPGA with bSOM

Tri-state Self Organizing Map (bSOM), which takes binary inputs and maintains tri-state weights, has been used for classification rather than clustering in this paper. The major contribution here is the demonstration of the potential use of the modified bSOM in security surveillance, as a recognition system on FPGA

FPGA-based Anomalous trajectory detection using SOFM

A system for automatically classifying the trajectory of a moving object in a scene as usual or suspicious is presented. The system uses an unsupervised neural network (Self Organising Feature Map) fully implemented on a reconfigurable hardware architecture (Field Programmable Gate Array) to cluster trajectories acquired over a period, in order to detect novel ones. First order motion information, including first order moving average smoothing, is generated from the 2D image coordinates (trajectories). The classification is dynamic and achieved in real-time. The dynamic classifier is achieved using a SOFM and a probabilistic model. Experimental results show less than 15\% classification error, showing the robustness of our approach over others in literature and the speed-up over the use of conventional microprocessor as compared to the use of an off-the-shelf FPGA prototyping board

Autonomous real-time surveillance system with distributed IP cameras

An autonomous Internet Protocol (IP) camera based object tracking and behaviour identification system, capable of running in real-time on an embedded system with limited memory and processing power is presented in this paper. The main contribution of this work is the integration of processor intensive image processing algorithms on an embedded platform capable of running at real-time for monitoring the behaviour of pedestrians. The Algorithm Based Object Recognition and Tracking (ABORAT) system architecture presented here was developed on an Intel PXA270-based development board clocked at 520 MHz. The platform was connected to a commercial stationary IP-based camera in a remote monitoring station for intelligent image processing. The system is capable of detecting moving objects and their shadows in a complex environment with varying lighting intensity and moving foliage. Objects moving close to each other are also detected to extract their trajectories which are then fed into an unsupervised neural network for autonomous classification. The novel intelligent video system presented is also capable of performing simple analytic functions such as tracking and generating alerts when objects enter/leave regions or cross tripwires superimposed on live video by the operator