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Object Detection and Accurate Localization in Industrial Application

Author: TianYu
Tutor: WangLin
School: Shanghai Jiaotong University
Course: Pattern Recognition and Intelligent Systems
Keywords: Target detection Hough transform Image registration ICP Graph Matching
CLC: TP391.41
Type: Master's thesis
Year: 2012
Downloads: 28
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Abstract


Computer Vision seventies of last century the rise of disciplines in the industry , due to the ease of use of the visual sensor , information - rich as well as low cost , making more and more visual - based industrial tasks . Based on the visual target detection need to be extracted from the image unchanged elements , usually through a stable point feature or image template encoding to achieve . Targeting close target detection and inconsistent task can be completed in target detection rough positioning accuracy industrial applications often demanding requirements of high-precision targeting belonging to image registration areas , due to noise , the presence of light and other factors , but also for image registration challenges, derivative image registration algorithm for different angles . Review and summarize the papers on a common target detection and image registration algorithm , improvements to existing algorithms , designed and implemented for industrial applications fast , robust target detection and precise image registration algorithm . The main contents of the paper and the results are as follows : 1 . Rapid target detection algorithms for industrial applications . Summed up the popular feature-based and template matching algorithm to improve the work of their predecessors for industrial applications target texture less fast algorithm to simultaneously detect multiple targets , learning by introducing training step robust template binding Robust templates voting mechanism , the plurality of objects within the image can be detected within 100 milliseconds . 2 for industrial applications sub-pixel registration algorithm . Summarizes the image gradation based on the Lucas-Kanade framework based on an image of spatial information ICP framework , for industrial applications the speed requirements , this paper introduces a different distance metrics and to optimize the objective function, the introduction of a new dimension to the data points in the ICP algorithm accelerated image registration , combined with the KD-tree coding , to achieve the sub-pixel detection of less texture objects . Graph-Matching Algorithm Based on the previous proposed a new mathematical model , and used for target detection . Summarizes the traditional GA algorithm based optimization algorithm framework , combined with the projection matrix SMAC algorithm proposed improvements , and to achieve a target detection system based on Graph-Matching algorithm .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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