Segmenting images with complex textures by using hybrid algorithm

Yuexing Han; Chuanbin Lai; Bing Wang; Hui Gu

doi:10.1117/1.JEI.28.1.013030

7 February 2019 Segmenting images with complex textures by using hybrid algorithm

Yuexing Han, Chuanbin Lai, Bing Wang, Hui Gu

Author Affiliations +

Journal of Electronic Imaging, Vol. 28, Issue 1, 013030 (February 2019). https://doi.org/10.1117/1.JEI.28.1.013030

Abstract

Application of computer images processing technology to analyze materials microstructural images, particularly metallographic images, has received increasing attention. The metallographic images contain the mesoscopic information on structural relation and components of materials. Quantitative analysis of these images can help to correlate the materials structures to their performance and properties at various levels. There are two challengeable issues necessary to be resolved, i.e., automatic segmentation and classification of different microscopic structures in metallographic images. Since the metallographic images often contain complex textures, the segmentation of them is usually inaccurate with present methods. We propose a hybrid algorithm, which combines the Gaussian filter, the mean shift method, the FloodFill, the improved flow-based difference-of-Gaussians, and the clustering to resolve the issues. The experiment results and the comparative results show that our method is effective to segment and classify the microstructural elements in metallographic images with complex textures.

Citation Download Citation

Yuexing Han, Chuanbin Lai, Bing Wang, and Hui Gu "Segmenting images with complex textures by using hybrid algorithm," Journal of Electronic Imaging 28(1), 013030 (7 February 2019). https://doi.org/10.1117/1.JEI.28.1.013030

Received: 27 August 2018; Accepted: 10 January 2019; Published: 7 February 2019

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