Paper
22 March 2019 Image segmentation with searching tree of superpixel boundaries
Eisaku Ono, Ikuko Shimizu
Author Affiliations +
Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 110493V (2019) https://doi.org/10.1117/12.2521577
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore
Abstract
Image segmentation is one of the most important techniques in computer vision and image processing. Many image segmentation methods have been proposed for these few decades. Hierarchical Feature Selection (HFS)1 is a graph-based approach for the image segmentation. It is known as a fast segmentation method that merges over segmented regions hierarchically. At the first level of the merge, the superpixels are utilized to obtain the over segmented regions. However, HFS sometimes fails when it is applied for the textured regions. In this paper, we propose a new approach for image segmentation, Searching Tree Segmentation from Superpixel (STSS), by formulating the merge of superpixels as a path searching problem. We construct trees and search the trees whose nodes correspond to the boundary of the superpixels and values of the nodes correspond to the distance between superpixels. Our algorithm does not check the boundaries of similar superpixels if these are no neighboring boundaries of the distinctively different superpixels to prevent the over segmentation of the textured regions, while HFS checks all boundaries including quite similar superpixels.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Eisaku Ono and Ikuko Shimizu "Image segmentation with searching tree of superpixel boundaries", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110493V (22 March 2019); https://doi.org/10.1117/12.2521577
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KEYWORDS
Image segmentation

Image processing algorithms and systems

RGB color model

Image processing

Computer vision technology

Feature selection

Machine vision

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