2 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 2 / 2
Yayın Optimisation of pedestrian detection system using FPGA-CPU hybrid implementation for vehicle industry(Inderscience Enterprises Ltd., 2019) Özcan, Ahmet Remzi; Tavşanoǧlu, Ahmet VedatImproved image processing and developing technologies are rapidly expanding the application areas of image processing systems. In recent years, pedestrian detection systems have become one of the major safety technologies used in the automotive industry. This paper presents an optimised real-time pedestrian detection system using an FPGA-CPU based hybrid design. The histograms of oriented gradients (HOG) algorithm, which is extensively used for feature extraction in pedestrian detection applications, was implemented on a low-end FPGA. In the study, the original HOG descriptors are designed in low complexity without sacrificing performance. The obtained features were classified on a low-power single board computer with support vector machine (SVM). Tests with the INRIA pedestrian database show that the proposed model has high potential for use as a real-time low-cost pedestrian detection system in practice.Yayın Sperm motility analysis system implemented on a hybrid architecture to produce an intelligent analyzer(Elsevier Ltd, 2020) Şavkay, Osman Levent; Yalçın, Müştak Erhan; Tavşanoğlu, Ahmet VedatMuch research and analysis in biomedicine involve image and video inspection using microscopes. Presently, scientists are dissatisfied with manual observations and assessments, when objective and enhanced data can be obtained by applying new technologies (such as image and video inspection) to biomedical fields, such as sperm analysis. Computer Assisted Sperm Analysis (CASA) systems, developed in the late 1980s, constitute third-generation methods of sperm analysis. This study aimed to develop a standalone medical image and video analysis system that is reconfigurable, flexible, reliable, deterministic, and robust. It proposed a new sperm motility analysis system running on a dual core Central Processing Unit (CPU) + field programmable gate arrays (FPGA) platform, under a real-time operating system (RTOS), which is a step ahead of the third-generation CASA systems. The system hardware and related sperm detection and tracking algorithms were the novelty of this work. The image processing functions mainly run on FPGA, image acquisition, and calculations run on CPU, parallel with FPGA. The result is a much faster, reliable, reconfigurable, and compact intelligent analyzer system. Our prototype system was applied to sperm motility analysis; however, other image processing systems can be applied to this architecture. Additionally, the proposed tracking method for sperm track determination is simple, effective, and does not exert a load on the system.
