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Abstract-This paper presents an application domain driven approach to the design of embedded systems on silicon, and it shows how this approach is used to design a chip for a multiwindow TV application. We discuss all major design steps in a logical order starting with an application domain analysis. This lead to the choice of Kahn data flow graphs as the programming paradigm for high-throughput signal applications. Based on this analysis we designed a multiprocessor architecture which uses run-time reconfiguration. Finally, attention is spent toward the physical implementation and the deep-submicron problems we had to solve. The result is a chip that can manage up to 25 internal real-time video streams. The chip combines the flexibility of a programmable solution with the cost effectiveness of a consumer product.

In this paper we attempt to generalize a sharpness enhancement technique for TV applications. Basically, the enhancement is accomplished by adding overshoot to luminance edges. However, the optimal amount of overshoot added for a high image quality depends on the local image statistics. For this purpose, four properties of the video signal are analysed locally by separate units and depending on this analysis, we regulate the amount of sharpness enhancement to be provided. Due to these additional controls, the system is robust with respect to varying image statistics and yields a high performance.

The CANDELA project aims at realizing a system for real-time image processing in traffic and surveillance applications. The system performs segmentation, labels the extracted blobs and tracks their movements in the scene. Performance evaluation of such a system is a major challenge since no standard methods exist and the criteria for evaluation are highly subjective. This paper proposes a performance evaluation approach for video content analysis (VCA) systems and identifies the involved research areas. For these areas we give an overview of the state-of-the-art in performance evaluation and introduce a classification into different semantic levels. The proposed evaluation approach compares the results of the VCA algorithm with a ground-truth (GT) counterpart, which contains the desired results. Both the VCA results and the ground truth comprise description files that are formatted in MPEG-7. The evaluation is required to provide an objective performance measure and a mean to choose between competitive methods. In addition, it enables algorithm developers to measure the progress of their work at the different levels in the design process. From these requirements and the state-of-the-art overview we conclude that standardization is highly desirable for which many research topics still need to be addressed.

Many proposed video content analysis algorithms for surveillance applications are very computationally intensive, which limits the integration in a total system, running on one processing unit (e.g. PC). To build flexible prototyping systems of low cost, a distributed system with scalable processing power is therefore required. This paper discusses requirements for surveillance systems, considering two example applications. From these requirements, specifications for a prototyping architecture are derived. An implementation of the proposed architecture is presented, enabling mapping of multiple software modules onto a number of processing units (PCs). The architecture enables fast prototyping of new algorithms for complex surveillance applications without considering resource constraints.

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