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首页> 外文会议>Sixth International Conference on Quality Control by Artificial Vision May 19-22, 2003 Gatlinburg, Tennessee, USA >Constraining deformable templates for shape recognition
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Constraining deformable templates for shape recognition

机译：约束可变形模板以进行形状识别

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摘要

This paper addresses the problem of robust shape recognition in the presence of shape deformation as well as changes in part position, orientation and scale. Point Distribution Models (PDM) are deformable templates that have interesting features for industrial inspection tasks, since they are built by statistical analysis of a training set and they define a prototype shape as well a set of possible, acceptable deformations. To further improve their classification capabilities, these deformable templates are extended by adding a constraint on the amount of deformation. A constrained optimization procedure is proposed and successfully tested on an industrial inspection task.
机译：本文解决了在存在形状变形以及零件位置，方向和尺寸变化的情况下，形状识别功能强大的问题。点分布模型（PDM）是可变形模板，具有用于工业检查任务的有趣功能，因为它们是通过对训练集进行统计分析而构建的，并且它们定义了原型形状以及一组可能的可接受变形。为了进一步提高其分类能力，这些可变形模板通过添加变形量约束来扩展。提出了约束优化程序，并在工业检查任务上成功进行了测试。

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