Fibre Orientation and Void Distribution Analysis in Polymer Composite Structures Using Image Processing

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Year : 2026 | Volume : 14 | 02 | Page :
    By

    T. Suguna,

  • G. Reddy Hemantha,

  • Edwin Paul N E,

  • K. Jayasakthi,

  • M. Dharani,

  • Venkata Prasanth B,

  1. Associate Professor, Department of Electronics and Communication Engineering, Panimalar Engineering College, Chennai, Tamil Nadu, India
  2. Professor, Department of Electronics and Communication Engineering, Madanapalle Institute of Technology & Science (MITS), Deemed to be University, Madanapalle, Andhra Pradesh, India
  3. Professor, Department of Mechanical Engineering, GRT Institute of Engineering and Technology, Tiruttani, Tamil Nadu, India
  4. Assistant Professor, Department of Electronics and Communication Engineering, KCG College of Technology, Chennai, Tamil Nadu, India
  5. Associate Professor, Department of Electronics and Communication Engineering, School of Engineering, Mohan Babu University, Tirupati, Andhra Pradesh, India
  6. Professor, Department of Electrical and Electronics Engineering, QIS College of Engineering & Technology, Ongole, Andhra Pradesh, India

Abstract

Fibre orientation and void distribution are critical microstructural features that govern the mechanical performance and reliability of polymer composite materials. Accurate and simultaneous characterisation of these features remains challenging due to their complex spatial interactions and dependence on processing conditions. In this work, an integrated image-processing framework is proposed for the quantitative analysis of fiber orientation and void distribution in polymer composite structures. High-resolution composite microstructure images are processed through a unified pipeline involving preprocessing, segmentation, orientation tensor computation, and void morphology analysis. Fiber alignment is quantified using orientation tensors and anisotropy indices, while void characteristics are described through volume fraction, equivalent diameter, aspect ratio, and spatial clustering metrics. The results demonstrate clear differentiation between samples with varying microstructural states, revealing a coupled relationship between reduced fiber alignment and increased void size and clustering. Performance evaluation confirms reliable segmentation accuracy, low orientation estimation error, and strong repeatability. The proposed approach enables comprehensive microstructural characterisation using a single analytical framework and provides physically interpretable descriptors that support improved understanding of structure–processing relationships in polymer composite systems.

Keywords: Polymer composites; Fiber orientation; Void distribution; Image processing; Microstructural characterisation.

How to cite this article:
T. Suguna, G. Reddy Hemantha, Edwin Paul N E, K. Jayasakthi, M. Dharani, Venkata Prasanth B. Fibre Orientation and Void Distribution Analysis in Polymer Composite Structures Using Image Processing. Journal of Polymer & Composites. 2026; 14(02):-.
How to cite this URL:
T. Suguna, G. Reddy Hemantha, Edwin Paul N E, K. Jayasakthi, M. Dharani, Venkata Prasanth B. Fibre Orientation and Void Distribution Analysis in Polymer Composite Structures Using Image Processing. Journal of Polymer & Composites. 2026; 14(02):-. Available from: https://journals.stmjournals.com/jopc/article=2026/view=242327


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Ahead of Print Subscription Original Research
Volume 14
02
Received 25/02/2026
Accepted 14/03/2026
Published 30/04/2026
Publication Time 64 Days
50

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