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Deep Texton-Coherence Network for Camouflaged Object Detection

Authors:

Zheng-Jun ZhaAuthors Info & Claims

IEEE Transactions on Multimedia, Volume 25

Pages 5155 - 5165

https://doi.org/10.1109/TMM.2022.3188401

Published: 04 July 2022 Publication History

Abstract

Camouflaged object detection is a challenging visual task since the appearance and morphology of foreground objects and background regions are highly similar in nature. Recent CNN-based studies gradually integrated the high-level semantic information and the low-level local features of images through hierarchical and progressive structures to achieve camouflaged object detection. However, these methods ignore the <bold>spatial statistical properties</bold> of the local context, which is a critical cue for distinguishing and describing camouflaged objects. To address this problem, we propose a novel Deep Texton-Coherence Network (DTC-Net) that leverages the spatial organization of textons in the foreground and background regions as discriminative cues for camouflaged object detection. Specifically, a Local Bilinear module (LB) is devised to obtain the robust representation of texton to trivial details and illumination changes, by replacing the classic first-order linearization operations with bilinear second-order statistical operations in the convolution process. Next, these texton representations are associated with a Spatial Coherence Organization module (SCO) to capture irregular spatial coherence via a deformable convolutional strategy, and then the descriptions of the textons extracted by the LB module are used as weights to suppress features that are spatially adjacent but have different representations. Finally, the texton-coherence representation is integrated with the original features at different levels to achieve camouflaged object detection. Evaluation on the three most challenging camouflaged object detection datasets demonstrats the superiority of the proposed model when compared to the state-of-the-art methods. Furthermore, our ablation studies and performance analyses demonstrate the effectiveness of the texton-coherence module.

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Cited By

Liu YZhang XZhu JTan P(2025)Improving underwater camouflage object segmentation with dual-decoder attention networkThe Journal of Supercomputing10.1007/s11227-024-06584-x81:1Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1007/s11227-024-06584-x
Zhou XWu ZCong R(2024)Decoupling and Integration Network for Camouflaged Object DetectionIEEE Transactions on Multimedia10.1109/TMM.2024.336071026(7114-7129)Online publication date: 31-Jan-2024
https://dl.acm.org/doi/10.1109/TMM.2024.3360710
Lyu YZhang HLi YLiu HYang YYuan D(2024)UEDG:Uncertainty-Edge Dual Guided Camouflage Object DetectionIEEE Transactions on Multimedia10.1109/TMM.2023.329509526(4050-4060)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMM.2023.3295095
Show More Cited By

Index Terms

Deep Texton-Coherence Network for Camouflaged Object Detection
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object detection
        Object recognition
      2. Computer vision tasks
  2. Machine learning
    1. Machine learning approaches
      1. Neural networks

Index terms have been assigned to the content through auto-classification.

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cover image IEEE Transactions on Multimedia

IEEE Transactions on Multimedia Volume 25, Issue

2023

8932 pages

ISSN:1520-9210

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1520-9210 © 2022 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.

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IEEE Press

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Published: 04 July 2022

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Cited By

Liu YZhang XZhu JTan P(2025)Improving underwater camouflage object segmentation with dual-decoder attention networkThe Journal of Supercomputing10.1007/s11227-024-06584-x81:1Online publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1007/s11227-024-06584-x
Zhou XWu ZCong R(2024)Decoupling and Integration Network for Camouflaged Object DetectionIEEE Transactions on Multimedia10.1109/TMM.2024.336071026(7114-7129)Online publication date: 31-Jan-2024
https://dl.acm.org/doi/10.1109/TMM.2024.3360710
Lyu YZhang HLi YLiu HYang YYuan D(2024)UEDG:Uncertainty-Edge Dual Guided Camouflage Object DetectionIEEE Transactions on Multimedia10.1109/TMM.2023.329509526(4050-4060)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1109/TMM.2023.3295095
Song XZhang PLu XHei XLiu R(2024)A Universal Multi-View Guided Network for Salient Object and Camouflaged Object DetectionIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2024.341760734:11_Part_1(11184-11197)Online publication date: 21-Jun-2024
https://dl.acm.org/doi/10.1109/TCSVT.2024.3417607

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