自动识别和组装拼图的快速图像比较方法

IF 1.9 4区 工程技术 Q2 Engineering
Yi-Wen Ke, Alan C. Lin
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引用次数: 0

摘要

本文提出了一种仅依靠图像处理和模板匹配技术,利用少量样本快速识别拼图的方法。在初步阶段,本文提出了一种分割方法,将拼图分割成具有局部特征的单个拼图块,获取每个拼图块的模板数据。随后,使用摄像头捕捉分散的拼图块,提取其轮廓,获得拼图图像数据。然后将拼图图像与模板数据进行匹配,在匹配过程中采用极坐标变换以减少计算时间。匹配过程还能识别拼图的数量和方向。最后,将匹配结果与机械臂集成,完成拼图组装任务。本文不仅概述了通过图像处理生成拼图图像数据和模板数据的方法,还详细阐述了在图像匹配过程中确定相应数量和方向的方法。本文通过不同类型的拼图验证了该方法的可行性,并考察了该方法在工业部件上的实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Rapid Image Comparison Approach to Automatic Recognition and Assembly of Jigsaw Puzzles

A Rapid Image Comparison Approach to Automatic Recognition and Assembly of Jigsaw Puzzles

This paper proposes a method for quick recognition of jigsaw puzzles using a small number of samples, solely relying on image processing and template matching techniques. In the preliminary stage, this paper proposes a segmentation approach to divide the jigsaw puzzle into individual pieces with partial features, obtaining template data for each puzzle piece. Subsequently, scattered puzzle pieces are captured using a camera, and their contours are extracted to acquire puzzle image data. The puzzle images are then matched with the template data, employing polar coordinate transformation during the matching process to reduce computational time. The matching process also identifies the puzzle piece's number and orientation. Finally, the matching results are integrated with a robotic arm to complete the task of puzzle assembly. This paper not only outlines the generation of puzzle image data and template data through image processing but also elaborates on the determination of corresponding numbers and orientations during image matching. The feasibility of this method is validated through different types of puzzles, and its applicability to industrial parts is also examined for practicality.

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来源期刊
CiteScore
4.10
自引率
10.50%
发文量
115
审稿时长
3-6 weeks
期刊介绍: The International Journal of Precision Engineering and Manufacturing accepts original contributions on all aspects of precision engineering and manufacturing. The journal specific focus areas include, but are not limited to: - Precision Machining Processes - Manufacturing Systems - Robotics and Automation - Machine Tools - Design and Materials - Biomechanical Engineering - Nano/Micro Technology - Rapid Prototyping and Manufacturing - Measurements and Control Surveys and reviews will also be planned in consultation with the Editorial Board.
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