Moving Object Tracking Application: FPGA and Model Based Implementation Using Image Processing Algorithms

Abstract

With increased resource size, powerful DSP blocks and large on-chip memory, Field Programmable Gate Array (FPGA) devices play a major role as hardware platforms for implementing compute intensive video image processing applications. In this paper, image processing algorithms are used for tracking a moving video object. The image processing algorithms used are (a) Noisy video generation with random motion (b) Video image median filter (c) Video image back ground removal (d) Video image thresholding (e) Video image edge detection (f) Video image height and width calculation (g) Video image center computation (h) Video image and center image overlay. The image processing algorithms are developed initially byModel Based Design Approach using Simulink models of MATHWORK's MATLAB Tool. Then these algorithms are implemented on ALTERA CYCLONE-II FPGA device using TERASIC DE2 FPGA hardware kit and ALTERA QUARTUS-II software tool. The input video image is taken from a NTSC/PAL camera and processed in real time using the algorithms on the FPGA and the resulted tracked video image output is displayed on a VGA monitor.

FPGA-Based HD Camera System for the Micropositioning of Biomedical Micro-Objects Using a Contactless Micro-Conveyor

“…The pictures are received in 8-bits grayscale mode. The object detection is realized by employing the BS (Background Subtraction) algorithms [ 34 , 35 , 36 , 37 , 38 , 39 , 40 ]. The BS algorithm principle is described with Equation (2).…”

“…These methods, [ 34 , 35 , 36 , 37 , 38 , 39 , 40 ], are simple to implement and are computationally efficient. Therefore, these are good candidates for the embedded applications.…”

“…Therefore, it can be easily implemented on an appropriate microprocessor-based embedded platform. Moreover, it can also be easily translated into the VHDL and can be implemented on an appropriate FPGA [ 37 , 38 , 39 , 40 , 41 ].…”