Research Article Open Access

Characterization of Composite Structure Surface Uniformity using Interval Based Gradient Field Histogram Analysis of Thermographic Images (IGF-HA)

Mahmoud Zaki Iskandarani1
  • 1 Al-Ahliyya Amman University, Jordan

Abstract

This paper presents a new approach to composite surface characterization using Image Histogram Analysis as a function of Gradient Field. Image sequences are weighed and combined in order to present a pattern change in the thermal response of a tested composite structure. Reaction Injection Molding samples used and subjected to thermal energy to characterize their surface uniformity and any existing damage. A threshold value is used for the purpose of segmenting and separating damaged from undamaged areas in the tested composite structure. Gradient field analysis established the critical time at which the surface started to show damage and segmented the tested images into areas of concern. The resulting histograms cover four main regions of interest according to the gradient intensities as a function of time. Each region is divided into eight subsections according to the corresponding limit value, resulting in thirty two subsections. Correlation between region gradient field and its histogram resulted in uncovering of surface deformities as a function of surface area thermal storage. The process is modeled mathematically.

Journal of Computer Science
Volume 14 No. 6, 2018, 819-828

DOI: https://doi.org/10.3844/jcssp.2018.819.828

Submitted On: 22 April 2018 Published On: 25 May 2018

How to Cite: Iskandarani, M. Z. (2018). Characterization of Composite Structure Surface Uniformity using Interval Based Gradient Field Histogram Analysis of Thermographic Images (IGF-HA). Journal of Computer Science, 14(6), 819-828. https://doi.org/10.3844/jcssp.2018.819.828

  • 4,200 Views
  • 1,842 Downloads
  • 1 Citations

Download

Keywords

  • Histogram Equalization
  • Histogram Specification
  • Gradient Norm
  • Edge Detection
  • Gray Level Mapping
  • Information Entropy
  • Segmentation