An FPGA-Based Real-Time Human Eye Pupil Detection System Using E2V Smart Camera
S. Navaneethan, N. Nandhagopal, V. Nivedita · Journal of Computational and Theoretical Nanoscience · 2019
Threshold based pupil detection algorithm was found tobe most efficient method to detect human eye. An implementation of a real-time system on an FPGA board to detect and track a human's eye is the main motive to obtain from proposed work. The Pupil detection algorithm involved thresholding and image filtering. The Pupil location was identified by computing the center value of the detected region. The proposed hardware architecture is designed using Verilog HDL and implemented on aAltera DE2 cyclone II FPGA for prototyping and logic utilizations are compared with Existing work. The overall setup included Cyclone II FPGA, a E2V camera, SDRAM and a VGA monitor. Experimental results proved the accuracy and effectiveness of the hardware realtime implementation as the algorithm was able to manage various types of input video frame. All calculation was performed in real time. Although the system can be furthered improved to obtain better results, overall the project was a success as it enabled any inputted eye to be accurately detected and tracked.