This work proposes an embedded system to detect pedestrians using reconfigurable computing making the image acquisition through a mono-camera attached to a vehicle in an urban environment. This work is motivated by the need to reduce the number of traffic accidents, even with government support, each year hundreds of people become victims thus bringing great damage to the economy. As a result, there is also a global concern of scientists to promote economically viable solutions that will contribute to reducing these accidents. A significant issue is related to the speed of response of the human brain to recognize and or to make decisions in situations of danger. This feature generates a demand for technological solutions aimed at helping people to drive vehicles in several respects. The system hardware was developed in FPGA and divided into interconnected blocks. First, for the pretreatment of the video, was built a block for data conversion from the camera to grayscale, then a simplified block for vertical stabilization dynamic video. To detection, two blocks were built, one for binary motion detection and one for a BLOB detection. To classify, was built one block to identify the size of the object in motion by the proportionality and making the selection. The tests in real environment of this system showed great results for a maximum speed of 30 km / h.

Dedico este trabalho aos meus pais Antonio Sérgio (in memorian) e Maria Célia, com todo meu amor e gratidão por tudo que me proporcionaram ao longo da vida. Desejo ser merecedor dessa dedicação incansável, especialmente quanto à minha formação. Palavras-chave: CoProjeto, ADAS, Sistemas Embarcados, Hardware. ABSTRACT MARTINEZ, L. A. Hardware and software codesign framework for camera-based advanced driver assistance systems. 2017. 130 p. Tese (Doutorado em Ciências -CiênciasThe demand for new technologies, enhanced security and comfort for urban cars has grown considerably in recent years prompting the industry to create systems designed to support drivers (ADAS -Advanced Driver Assistance Systems). This fact contributed to the development of many embedded systems in the automotive area among them, the pedestrians collision avoidance. Through the advancement in various research, began circulating through the streets vehicles with anti-collision systems and autonomous navigation. However, to achieve ever more challenging goals, designers need tools to unite technology and expertise from different areas efficiently. In this context, there is a demand for building systems that increase the level of abstraction of models of image processing for use in embedded systems enabling better design space exploration. To help minimize this problem, this research demonstrates a develop a specific framework for hardware/software codesign to build ADAS systems using computer vision. The framework aims to facilitate the development of applications, allowing better explore the design space, and thus contribute to a performance gain in the development of embedded systems in relation to building entirely in hardware. One of the requirements of the project is the possibility of the simulation of an application before synthesis on a reconfigurable system. The main challenges of this system were related to the construction of the intercommunication system between the various Intellectual Property (IP) blocks and the software components, abstracting from the end user numerous hardware details, such as memory management, interruptions, cache, types (Floating point, fixed point, integers) and so on, enabling a more user-friendly system for the designer.

Este artigo apresenta um framework para co-projeto de hardware e software para a construção de sistemas destinados ao apoio de motoristas utilizando visão computacional. Este trabalho faz parte de um projeto de pesquisa de doutorado em fase de conclusão. Para sua validação, um sistema modular de detecção de pedestres é implementado comparando-se os resultados obtidos com outro projeto.

No abstract