The Design And Implementation Of Identification Of Pointer Instrument Based On FPGA

In the current industry, the application of pointer instrument is very common in the production and usage. Most applications take the way of artificial reading to collect the pointer instrument data, but some operation environment is harsh and dangerous, it is high temperature, high voltage and high radiation.Compared to the traditional instrument identification methods, pointer instrument automatic identification technology is based on FPGA (Field Programmable Gate Array) within comparable advantages. It can realize automatic capture, analysis, processing and recognition with the full use of the advantage of the parallelism on hardware. Thus, it can improve the effect of image processing.This paper describes the design of a pointer instrument identification system based on FPGA, using Altera’s DE2development board as hardware platform, SDRAM (Synchronous Dynamic RAM, synchronous dynamic random access memory) for image storage, VGA (Video Graphic Array, VGA) device displays pointer instrument images after pre-processing. The whole system adopts software and hardware design method. Hardware:firstly, the system designs and realizes every module on the basis of overall demand analysis, including image acquisition module, SDRAM module, image display module and pointer image pre-processing module. Under Quartus II software and hardware design language this paper sets up the hardware system. The system can use its SOPC Builder to build the Pointer module as a follow-up analysis of operational platform. Pointer identification module extract pointer by Hough, the pointer data to show the number of decision module. Shows the number of modules is determined angle method to calculate the pointer shows the number of stores and displays the result on the LCD screen.Experiments show that the system can achieve the basic function of pointer instrument identification system, and it completed the design of the system. After testing, the system works normally, stablly, adaptably and safely. Through analysis and improvement of the algorithm, the system improves the recognition accuracy effectively.