Solving Jigsaw Puzzle of Large Eroded Gaps Using Puzzlet Discriminant Network

Xingke Song, Xiaoying Yang, Jianfeng Ren, Ruibin Bai, Xudong Jiang

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Solving Jigsaw puzzles has recently become an emerging research topic. Traditionally, boundary similarities are utilized for puzzle reassembly. In this paper, we solve Jigsaw Puzzles of Large Eroded Gaps (JPLEG), where boundary similarities are weak and image semantics are the only feasible clues. Inspired by human strategy in solving a puzzle, we introduce the concept of puzzlet, where fragments are gradually combined to form puzzlets of different sizes until the completion of the puzzle. Two sets of Puzzlet Discriminant Networks are designed to visually perceive whether these puzzlets are correctly reassembled. The puzzle reassembly is then formulated as a combinatorial optimization problem, and solved using a genetic algorithm. The proposed method is evaluated on two large datasets, which shows that it significantly outperforms the state-of-the-art methods for puzzle solving.

Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728163277
DOIs
Publication statusPublished - 2023
Event48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023 - Rhodes Island, Greece
Duration: 4 Jun 202310 Jun 2023

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
Country/TerritoryGreece
CityRhodes Island
Period4/06/2310/06/23

Keywords

  • Combinatorial Optimization
  • Genetic Aglorithm
  • Puzzle Reassembly
  • Puzzlet Discriminant Network

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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