Desenvolvimento de hadware reconfigurável utilizando o processador intel/altera Nios II softcore para execução do algoritmo de detecção de face de Viola-Jones - NASCIMENTO JUNIOR, Francisco Carrera (2019)
The use of computational mechanisms, more precisely those that approach the concepts of computer vision, are of great relevance being widely applied in areas such as biometric identification, detection and recognition of objects. Some works show these applications as in the identification of faces (CHE; CHANG, 2010) and eyes (MANNAY; ABID, 2015). For the processing of the images, devices that have high computational power are required, thus the development of embedded systems using the reconfigurable computing paradigm (RC), such as the FPGA (Field Programmable Gate Array), is promising in this context. Unlike other approaches such as Application Specific Integrated Circuits (ASICs) where hardware is developed that can not subsequently be reprogrammed, FPGAs provide flexibility in the development of specific functionalities. Therefore, when future design updates and upgrades to new technologies are required, it offers the developer the option of synthesizing a new hardware description (HDL). In the face of the advantages offered by FPGAs, we adopted the same with the objective of performing the facial detection process, and opted for the use of a customizable Intel/Altera Nios II processor, SDRAM (Synchronous Dynamic Random Access Memory) and other components necessary for the operation of the system, which will be responsible for storing and executing the algorithm responsible for said detection. We use the algorithm proposed by (VIOLA; JONES, 2001), developed in C/C++, to perform the image processing and indicate the presence or absence of one or more faces. After the system development and integration of the algorithm, executions were performed with the reading of images previously stored in the computer and transmitted to the FPGA and also the capture from the Terasic TRDB-D5M camera. It was observed the behavior of face detections in several images with characteristics such as face in normal position, inclined, with and without the use of glasses, different formats of face and hair. We succeeded in executing the scenarios presented, as well as the detection and demarcation of the faces locations.