Share Email Print

Proceedings Paper

Dense learning by high dimensional SOMs composed of input-output fusion vectors for interactive image segmentation
Author(s): Hotaka Takizawa
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

This study proposes an interactive image segmentation method based on high dimensional self organizing maps (SOMs). The proposed method was applied to gray-scale and color images. The experimental results demonstrated that higher dimensional SOMs were able to achieve more accurate segmentation.

Paper Details

Date Published: 22 March 2019
PDF: 6 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110492L (22 March 2019); doi: 10.1117/12.2520491
Show Author Affiliations
Hotaka Takizawa, Univ. of Tsukuba (Japan)

Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?