English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Traditional level sets suffer from two major limitations: 1) unable to detect touching object boundaries and 2) segment partially occluded objects. In this paper, we present a model and simulation of a level set functional with unified knowledge of objects region, boundary, and shape models. The simulations of the proposed model were tested on high-speed videos of the train rolling stock for bogie part segmentation. The proposed model will resolve single- and multi-object segmentation of touching boundaries and partially occulted mechanical parts on a train bogie. Simulations on high-speed videos of four trains with 1 0720 frames have resulted in near perfect segmentation of 10 touching and occluded bogie parts. The proposed model performed better than the state-of-the-art level set segmentation models, showing faster and more accurate segmentations of moving mechanical parts in high-speed videos.

Unifying Boundary, Region, Shape into Level Sets for Touching Object Segmentation in Train Rolling Stock High Speed Video