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Article

Vision-Based Jigsaw Puzzle Solving with a Robotic Arm

Department of Electrical Engineering, Yuan Ze University, Taoyuan 32003, Taiwan
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Author to whom correspondence should be addressed.
Sensors 2023, 23(15), 6913; https://doi.org/10.3390/s23156913
Submission received: 15 June 2023 / Revised: 31 July 2023 / Accepted: 1 August 2023 / Published: 3 August 2023
(This article belongs to the Special Issue Artificial Intelligence in Imaging Sensing and Processing)

Abstract

This study proposed two algorithms for reconstructing jigsaw puzzles by using a color compatibility feature. Two realistic application cases were examined: one involved using the original image, while the other did not. We also calculated the transformation matrix to obtain the real positions of each puzzle piece and transmitted the positional information to the robotic arm, which then put each puzzle piece in its correct position. The algorithms were tested on 35-piece and 70-piece puzzles, achieving an average success rate of 87.1%. Compared with the human visual system, the proposed methods demonstrated enhanced accuracy when handling more complex textural images.
Keywords: edge similarity; Hausdorff distance; patch reconstruction; puzzle solving; robotic arm; template matching edge similarity; Hausdorff distance; patch reconstruction; puzzle solving; robotic arm; template matching

Share and Cite

MDPI and ACS Style

Ma, C.-H.; Lu, C.-L.; Shih, H.-C. Vision-Based Jigsaw Puzzle Solving with a Robotic Arm. Sensors 2023, 23, 6913. https://doi.org/10.3390/s23156913

AMA Style

Ma C-H, Lu C-L, Shih H-C. Vision-Based Jigsaw Puzzle Solving with a Robotic Arm. Sensors. 2023; 23(15):6913. https://doi.org/10.3390/s23156913

Chicago/Turabian Style

Ma, Chang-Hsian, Chien-Liang Lu, and Huang-Chia Shih. 2023. "Vision-Based Jigsaw Puzzle Solving with a Robotic Arm" Sensors 23, no. 15: 6913. https://doi.org/10.3390/s23156913

APA Style

Ma, C.-H., Lu, C.-L., & Shih, H.-C. (2023). Vision-Based Jigsaw Puzzle Solving with a Robotic Arm. Sensors, 23(15), 6913. https://doi.org/10.3390/s23156913

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