Real Time Vision Guided Roboti System Featuring FPGA Technology For Ima E Processing

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Date
2006-02
Authors
Akbar, Bharmal Muhammedali
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Abstract
Since the early 80s computer vision h s been extensively applied in the field of food processing, quality evaluation, and packaging so as to release human labourers from this tedious task and th reby increasing factory throughput and consistency. Complete robotic automati n for handling and packaging of food products improves food hygiene while s isfying operation safety standards such as Hazard Analysis and Critical Co trol Points (HACCP). The most important aspect for an efficient automated ystem in the food industry is its vision feed-back system. Two essential aspe ts for an efficient real time vision system are, firstly it should accurately detect he position of single and isolated objects as well as overlapping or occluding od objects so as to provide the robot with information to position itself accu tely in order to manipulate that object. Secondly the image processing result should be computed at real-time and made available to the robot. This project integrates the modified of the Hough transform algorithm along with contour centroid detectio method as the main recognition engine. This method accurately detects the osition of top-most object even under severely overlapping cases, thus provid g the robot with accurate object position details. Vision programs consist of mplex mathematical calculations and number of repetitive instructions for each image pixel. Implementing such programs on the general purpose processor PP) used in the desktop computer for this project took an average of 5 seco ds to provide the results. This is primarily because the GPP execute instructi s sequentially in multiplexed timesharing manner. Dedicated hardware such s FPGA chip carry out real-time concurrent processing on customized hardw e architecture to achieve real-time computation speeds. For the image processi g algorithm, the data-independent modules were identified for implementing hem in concurrent processes to enhance computations speeds. The embed ed hardware is interfaced to the PC's parallel port. The image processing algorithm's me ods and procedures were tested on commercially available burgers. The al orithm was successfully able to identify the top-most minimally overlapped nd maximally exposed specie of burger from the heap of burgers with an accur cy of 98%. The implementation of the vision program on the FPGA chip helped i achieving computation speeds of 0.157 milliseconds for a 640X480 image with clock cycle of 12 nano-seconds with the customised FPGA design. Thus th dedicated hardware assisted in achieving real-time computation speeds as compared to the average of 5 seconds on the GPP used in this project.
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Complete robotic automation for , handling and packaging of food products
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