Automatic Filler Dispersion Quantification in Microstructure Images of Bottom Ash Reinforced Polymer Composite

Fajar Astuti Hermawati, I Made Kastiawan, Muhyin

Abstract

Distribution or dispersion analysis of polymer composite particle fillers is crucial to determine the material's properties and strengths. Bottom ash was used as reinforcement particles in the polymer composite. Bottom ash particles have an irregular shape, porous structure, and rough texture surface. The characteristics cause difficulty in detecting and analyzing the particles in the microstructure image of the polymer composite. This study aimed to build a robust method to detect bottom ash particles in the polymer composite automatically through microstructure image observation. The proposed method can also identify the agglomerated bottom ash particles, separate them, and analyze the distribution. Firstly, an image enhancement technique is applied to eliminate noise in the input image. A multi-level fuzzy segmentation method is implemented to obtain the filler particles region. Each particle region obtained is examined whether it is a touching particle and split it using an edge detection-based method. Before implementing the edge detection, the void filler algorithm is applied. We used a Prewitt edge detector that combines filling gaps between two broken segments using a round mask. The logic difference operation between the whole area and the resulting edge area is implemented to separate the touching particle region. At finally, the quantification of filler dispersion is carried out. To investigate the performance of the splitting method, we compared it with the watershed method.  In experiments, this touching particle splitting method can separate agglomeration particles with more than 90% accuracy. This study has two-fold novelties. Firstly, this pioneering study automatically identifies and quantifies filler particles with irregular shapes using image processing techniques. Second, the proposed splitting method has better performance than the watershed method used in previous studies.

 

Keywords: image processing, dispersion analysis, bottom ash particles, agglomeration particle, microstructure image.

 

 


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