A single-chip FPGA implementation of real-time adaptive background model

This paper demonstrates the use of a single-chip FPGA for the extraction of highly accurate background models in real-time. The models are based on 24-bit RGB values and 8-bit grayscale intensity values. Three background models are presented, all using a camcorder, single FPGA chip, four blocks of RAM and a display unit. The architectures have been implemented and tested using a Panasonic NVDS60B digital video camera connected to a Celoxica RC300 Prototyping Platform with a Xilinx Virtex II XC2v6000 FPGA and 4 banks of onboard RAM. The novel FPGA architecture presented has the advantages of minimizing latency and the movement of large datasets, by conducting time critical processes on BlockRAM. The systems operate at clock rates ranging from 57MHz to 65MHz and are capable of performing pre-processing functions like temporal low-pass filtering on standard frame size of 640X480 pixels at up to 210 frames per second

OPTIMIZED ARCHITECTURE DESIGN AND IMPLEMENTATION OF OBJECT TRACKING ALGORITHM ON FPGA

FPGA based Object tracking implementation is one of the most recent video surveillance applications in embedded systems. In general, FPGA implementation is more efficient than general purpose computers in attaining high throughput due to its parallelism and execution speed. The system need to be designed on a standard frame rate in such a way to achieve optimal performance in real time environment. Optimal design of a system is dependent on minimizing the cost, area (device utility) and power while achieving the required speed. Past research work that investigated object tracking systems' implementation on FPGA achieved a significantly high throughput but have shown high device utilization. This research work aims at optimizing the device utilization under real time constraints. The Adaptive Hybrid Difference algorithm (AHD), which is used to detect the moving objects, was chosen to be implemented on FPGA due to its computation ability and efficiency with regard to hardware implementation. AHD can work at various lighting conditions automatically by determining the adaptive threshold in every period of time

FPGA-Based Portable Ultrasound Scanning System with Automatic Kidney Detection

Bedsides diagnosis using portable ultrasound scanning (PUS) offering comfortable diagnosis with various clinical advantages, in general, ultrasound scanners suffer from a poor signal-to-noise ratio, and physicians who operate the device at point-of-care may not be adequately trained to perform high level diagnosis. Such scenarios can be eradicated by incorporating ambient intelligence in PUS. In this paper, we propose an architecture for a PUS system, whose abilities include automated kidney detection in real time. Automated kidney detection is performed by training the Viola–Jones algorithm with a good set of kidney data consisting of diversified shapes and sizes. It is observed that the kidney detection algorithm delivers very good performance in terms of detection accuracy. The proposed PUS with kidney detection algorithm is implemented on a single Xilinx Kintex-7 FPGA, integrated with a Raspberry Pi ARM processor running at 900 MHz

Traffic monitoring using image processing : a thesis presented in partial fulfillment of the requirements for the degree of Master of Engineering in Information and Telecommunications Engineering at Massey University, Palmerston North, New Zealand

Traffic monitoring involves the collection of data describing the characteristics of vehicles and their movements. Such data may be used for automatic tolls, congestion and incident detection, law enforcement, and road capacity planning etc. With the recent advances in Computer Vision technology, videos can be analysed automatically and relevant information can be extracted for particular applications. Automatic surveillance using video cameras with image processing technique is becoming a powerful and useful technology for traffic monitoring. In this research project, a video image processing system that has the potential to be developed for real-time application is developed for traffic monitoring including vehicle tracking, counting, and classification. A heuristic approach is applied in developing this system. The system is divided into several parts, and several different functional components have been built and tested using some traffic video sequences. Evaluations are carried out to show that this system is robust and can be developed towards real-time applications

Peptide mass fingerprinting using field-programmable gate arrays

The reconfigurable computing paradigm, which exploits the flexibility and versatility of field-programmable gate arrays (FPGAs), has emerged as a powerful solution for speeding up time-critical algorithms. This paper describes a reconfigurable computing solution for processing raw mass spectrometric data generated by MALDI-TOF instruments. The hardware-implemented algorithms for denoising, baseline correction, peak identification, and deisotoping, running on a Xilinx Virtex-2 FPGA at 180 MHz, generate a mass fingerprint that is over 100 times faster than an equivalent algorithm written in C, running on a Dual 3-GHz Xeon server. The results obtained using the FPGA implementation are virtually identical to those generated by a commercial software package MassLynx

The effects of destination image and perceived risk on revisit intention: a study in the south eastern coast of Sabah, Malaysia

This study investigated the effects of destination image and perceived risk on revisit intention in the South Eastern Coast of Sabah, Malaysia. A total of 171 questionnaires were collected from international tourists through a self-administered questionnaire. The result of this study identified that three dimensions of destination image (travel environment, natural attraction, entertainment, and events) had significant effects on revisit intention. However, perceived risk was not important to the tourists’ revisit intention. The findings have implications on the tourism industry, especially for key players such as the tourism board and travel companies. It also serves as a reference to destinations with a similar risk background