PHYSICS-BASED IMAGE SEGMENTATION USING FIRST ORDER STATISTICAL PROPERTIES AND GENETIC ALGORITHM FOR INDUCTIVE THERMOGRAPHY IMAGING

Abstract

Thermographic inspection has been widely applied to Non-Destructive Testing and Evaluation (NDT&E) with capabilities of rapid, contactless and large surface area detection. Image segmentation is considered essential for identifying and sizing defects. To attain a high level performance, specific physics-based models that describe defects generation and enable the precise extraction of target region are of crucial importance. In this paper, an effective genetic first order statistical image segmentation algorithm is proposed for quantitative crack detection. The proposed method automatically extracts valuable spatial-temporal patterns from unsupervised feature extraction algorithm and avoids a range of issues associated with human intervention in laborious manual selection of specific thermal video frames for processing. An internal genetic functionality is built into the proposed algorithm to automatically control the segmentation threshold to render enhanced accuracy in sizing the cracks. Eddy Current Pulsed Thermography (ECPT) will be implemented as a platform to demonstrate surface crack detection. Experimental tests and comparisons have been conducted to verify the efficacy of the proposed method. In addition, a global quantitative assessment index F-Score has been adopted to objectively evaluate the performance of different segmentation algorithms.

Existing System

Adaptive constraint propagation (ACP), first order statistical properties (FOSP)

Proposed System

This paper proposes a new method that incorporates the physics characteristics of defect behavior in IRT to derive the first order statistical properties (FOSP) of defect segmentation and utilizes the genetic algorithm to automatically adapt the statistical features for further optimization of the threshold selection. The proposed method has consistent performance and strong de-noising capability. The comparison in terms of the F-score has been undertaken for different segmentation algorithms through the real experiments. Experimental tests on man-made metal defects and natural defects have been conducted to show the validity of the proposed algorithm. 

Architecture