@article{(Open Science Index):https://publications.waset.org/pdf/883,
	  title     = {FPGA Implementation of a Vision-Based Blind Spot Warning System},
	  author    = {Yu Ren Lin and  Yu Hong Li},
	  country	= {},
	  institution	= {},
	  abstract     = {Vision-based intelligent vehicle applications often require large amounts of memory to handle video streaming and image processing, which in turn increases complexity of hardware and software. This paper presents an FPGA implement of a vision-based blind spot warning system. Using video frames, the information of the blind spot area turns into one-dimensional information. Analysis of the estimated entropy of image allows the detection of an object in time. This idea has been implemented in the XtremeDSP video starter kit. The blind spot warning system uses only 13% of its logic resources and 95k bits block memory, and its frame rate is over 30 frames per sec (fps).
},
	    journal   = {International Journal of Mechanical and Mechatronics Engineering},
	  volume    = {4},
	  number    = {12},
	  year      = {2010},
	  pages     = {1452 - 1456},
	  ee        = {https://publications.waset.org/pdf/883},
	  url   	= {https://publications.waset.org/vol/48},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 48, 2010},
	}