Research And Implementation Of Edge Feature Matching Algorithm Based On Zynq-7000

The location and identification of target are important parts of machine vision research.The applications of location and identification in the production line can not only achieve accurate and real-time identification which is online to improve production efficiency but also conducive to the production of information management to adapt to the changes in the form of modern production better.Template matching,an effective method in the field of target's location and identification,has been widely used in workpiece localization,defect detection,target tracking.However,the common algorithm for template matching are not effective for the sensitive problems such as nonlinear illumination and occlusion,as well as the rotation and scaling of the target.The results are not ideal and can not be applied in complicated industrial production environments.The thesis choose the matching algorithm based on edge feature's gradient vector to research.It can be used to match objects because of the edge of the image which can directly reflect the contour and the insensitive property for nonlinear illumination.Based on the Xilinx Zynq-7000 platform,the matching algorithm of edge feature is split to the software part and the hardware part based on the software hardware co-designe.The edge detection module is implemented in the programmable logic part of the Zynq platform.The template training module and the image matching module are implemented in the processor system of the Zynq platform.It has high practical value to dynamically configure parameters such as the templated area,the search area by job file.The main contents of this thesis include the following aspects:(1)The thesis introduces the matching method which is commonly used at present,and describes the algorithm's matching principle,image pyramid acceleration search principle and the solution of template matching in rotation and scale in detail.(2)By studying the technical features and development process of Zynq platform and the theoretical knowledge of sobel edge extraction operator,implementing the hardware acceleration of edge extraction operation by using Vivado HLS which is high-level synthesis tools.(3)Through the background PC interface,we can configure related parameters included templated area,search area to generate job file based on xml format.Then we send the job file to the smart camera to resolve file data.The smart camera can dynamically modify the algorithm parameters in the image processing pipeline to achieve the adjustment of the algorithm functions.(4)Achieveing the software design for matching algorithm of edge feature in the Zynq-7000's ARM.It describes the implementation details such as the edge of the screening,the template processing under rotation,matching process.Finally,the algorithm is used in hardware and software joint test by the ZC702 to get the performance data with the nonlinear illumination,occlusion,rotation,scaling.The data shows that the matching algorithm based on edge feature's gradient vector meets the needs of the project.It can obtain good results in the nonlinear illumination,occlusion,rotation and scaling.