Post-segmentation processing based on image morphology

Zhiying Zhang; Chao Huang

doi:10.1117/12.2626564

20 December 2021 Post-segmentation processing based on image morphology

Zhiying Zhang, Chao Huang

Proceedings Volume 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021); 121550N (2021) https://doi.org/10.1117/12.2626564
Event: International Conference on Computer Vision, Application, and Design (CVAD 2021), 2021, Sanya, China

Abstract

The mainstream segmentation methods may suffer from problems in the separation of boundaries due to the presence of adhesion and overlapping. Therefore, subsequent processing is further required for segmentation tasks in different applications to obtain better performance. This paper proposes a post- segmentation processing method to solve the problem of boundary adhesion and overlapping. The method relies on morphological characteristics, which uses graphical rules to detect the target contour, find the adhesion area, and make judgments for separation. The proposed method is verified on post-segmentation processing of prediction masks of ore images, in which an improved U-Net model is firstly applied for ore image segmentation and then the proposed method is further applied for better boundary separation. The improved U-Net model segments the ores in pixel-level according to their types and output prediction masks of ore images. However, there are adhesions and overlaps among ores in the prediction masks. And our work strives to separate the adhered ore in the prediction masks. The experimental results show that our method is efficient in boundary separation.

Citation Download Citation

Zhiying Zhang and Chao Huang "Post-segmentation processing based on image morphology", Proc. SPIE 12155, International Conference on Computer Vision, Application, and Design (CVAD 2021), 121550N (20 December 2021); https://doi.org/10.1117/12.2626564

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KEYWORDS

Image segmentation

Image processing

Neural networks

Image processing algorithms and systems

Detection and tracking algorithms

Target detection

Binary data

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