광학 밀도 기반 이미지 정규화를 이용한 장기간 부식 시편 이미지 분석

Abstract

Corrosion of metals poses a threat to structural integrity in various industrial sectors and can intensify with prolonged exposure. This study proposes an efficient method for corrosion detection and analysis. A heuristic approach was used to derive a corrosion matrix composed of corrosion area colors and specimen surface colors, utilizing the CIEDE2000 color difference criterion. By converting specimen images into optical density space and performing color normalization, consistency in color changes was maintained during long-term observation. The combination of Optical Density transformation and HSV color space transformation provides an effective and consistent method for analyzing the corrosion process. This approach is expected to enhance the performance of corrosion monitoring systems and improve structural safety.