This paper presents a contribution to the development of rapid prototyping tools based on dataflow description. In this context, a major key goal is to propose a design flow which includes an automatic synthesis of the hardware interfaces. Therefore, this paper presents a methodology to define and generate automatically a system's interface from a data-flow description. To achieve such an ambitious goal, a generic hardware socket has been defined. This paper presents especially the serialization and de-serialization of different data flows between the hardware design and the physical interface. Different strategies are therefore compared and discussed.

Nowadays, high-speed imaging offers high investigation possibilities for a wide variety of applications such as motion study, manufacturing developments. Moreover, due to the electronic progresses, real-time processing can be implemented in the high-speed acquisition systems. Important information can be extracted in real-time from the image and then be used for on-line controls. Therefore we have developed a high-speed smart camera with high-speed CMOS sensor, typically 500 fps with a 1.3 Mega-pixels resolution. Different specific processing have been implemented inside an embedded FPGA according to the high-speed data-flow. The processing are mainly dedicated to feature extraction such as edge detection, or image analysis, and finally markers extraction and profilometry. In any case, the data processing allows to reduce the large data flow (6.55 Gbps) and to propose a transfer on a simple serial output link as USB 2.0. This paper presents the high-speed smart camera and focuses two processing implementations: the marker extraction and the related profilometry measurement. In the marker extraction mode, the center of mass is determined for each marker by a combination of image filtering. Only the position of the center is transferred via the USB 2.0 link. For profilometry measurements, a simplify algorithm has been implemented at low-cost in term of hardware resources. The positions of the markers or the different object's profiles can be determined in real-time at 500 fps with full resolution image. A higher image rate can be reached with a lower resolution (i.e. 500 000 profiles for a single row image).

This work describes an image acquisition and processing system based on a new co-processor architecture designed for CMOS sensor imaging. The platform permits to configure a wide variety of acquisition modes (random region acquisition, variable image size, multi-exposition image) as well as high-performance image pre-processing (filtering, de-noising, binarisation, pattern recognition). Furthermore, the acquisition is driven by an FPGA, as well as a processing stage followed by a Nexperia processor. The data transfer, from the FPGAs board to the Nexperia processor, can be pipelined to the co-processor to increase achievable throughput performances. The co-processor architecture has been designed so as to obtain a unit that can be configured on the fly, in terms of type and number of chained processing (up to 8 successive pre-defined pre-processing), during the image acquisition process that is dynamically defined by the application. Examples of acquisition and processing performances are reported and compared to classical image acquisition systems based on standard modular PC platforms. The experimental results show a considerable increase of the performances. For instance the reading of bar codes with applications to postal sorting on a PC platform is limited to about 15 images (letters) per second. The new platform beside resulting more compact and easily installable in hostile environments can successfully analyze up to 50 images/s.

High-speed video cameras are powerful tools for investigating for instance the biomechanics analysis or the movements of mechanical parts in manufacturing processes. In the past years, the use of CMOS sensors instead of CCDs has enabled the development of high-speed video cameras offering digital outputs, readout flexibility, and lower manufacturing costs. In this paper, we propose a high-speed smart camera based on a CMOS sensor with embedded processing. Two types of algorithms have been implemented. A compression algorithm, specific to high-speed imaging constraints, has been implemented. This implementation allows to reduce the large data flow (6.55 Gbps) and to propose a transfer on a serial output link (USB 2.0). The second type of algorithm is dedicated to feature extraction such as edge detection, markers extraction, or image analysis, wavelet analysis, and object tracking. These image processing algorithms have been implemented into an FPGA embedded inside the camera. These implementations are low-cost in terms of hardware resources. This FPGA technology allows us to process in real time 500 images per second with a 1280×1024 resolution. This camera system is a reconfigurable platform, other image processing algorithms can be implemented.

High-speed video cameras are powerful tools for investigating, for instance, fluid dynamics or the movements of mechanical parts in manufacturing processes. In the past 5 years the use of CMOS sensors instead of CCDs has facilited the development of high-speed video cameras offering digital outputs, readout flexibility, and lower manufacturing costs. Still the huge data flow provided by the sensor cannot be easily transferred or processed and thus must generally be stored temporarily in fast local RAM. Since this RAM is size limited, the recording time in the camera is only a few seconds long. We tried to develop an alternative solution that would allow continuous recording. We developed a real-time image compression in order to reduce the data flow. We tested three algorithms: run-length encoding, block coding, and compression using wavelets. These compression algorithms have been implemented into a FPGA Virtex II-1000 and allow real-time compression factors between 5 and 10 with a PSNR greater than 35dB. This compression factor allowed us to link a new high-speed CMOS video camera with a PC using a single USB2 connection. The full flow of 500 fps in 1280x1024 format is transferred to the computer in real-time.